Image Processing

The paper proposes a robust dual-microphone algorithm for Voice Activity Detection (VAD) suitable for detecting speech arriving from random directions. The algorithm is based on the use of higher order statistics (HOS) in the complex subband domain in order to effectively detect voicing segments and distinguish them from nonharmonic noise. Metrics based on new established properties of the 2 nd and 4 th -order cumulants of complex exponentials are derived. The pros and cons of each of these are analyzed and validated through simulation in various SNR conditions. The results show the proposed scheme is effective in discriminating voiced speech segments, and is robust to Gaussianlike and real-life recorded noises, even in low SNR.

In recent years, multispectral image fusion methods are viewed as an effective tool to analyze multiband remote sensing images. In this paper a novel hybrid multispectral image fusion method using combine framework of wavelet transform and fuzzy logic is proposed. The proposed method provides novel tradeoff solution between the spectral and spatial fidelity and preserves more detail spectral and spatial information. New hybrid image fusion rules are also proposed. Proposed method is applied on registered Panchromatic and Multispectral images and simulation results are compared with standard image fusion parameters. The simulation results of proposed method also compared with five different standard Pan sharpening methods available in literature. It has been observed from simulation results that proposed algorithm preserves better spatial and spectral information and better visual quality compared to earlier reported methods.

The image segmentation is the basic step in the image processing involved in the processing of medical images. Over the past two decades, medical image segmentation has remained a challenge for researchers while the use of this imaging modality is rapidly growing in research studies. This article surveys the techniques and their effect on chest Xray images. The objective of this work is to study the key similarities and differences among the different published methods while highlighting their strengths and weaknesses on chest X-ray images. The reason is to assist the researchers in the choice of an appropriate lung segmentation methodology. We additionally give a complete portrayal of the existing few basic methods when combined with preprocessing method that can be utilized as a part of the segmentation. A discussion and fair analysis justified with experimental results along with quantitative correlation of the outcomes on 247 images of JSRT through Dice coefficient exhibited.

Motion information scalability is an important requirement for a fully scalable video codec, especially in low bit rate or small resolution decoding scenarios, for which the fully scalable motion model (SMM) has been proposed. SMM can collaborate flawlessly with other scalabilities, such as spatial, temporal and quality, in a scalable video codec and it performs better than nonscalable motion model. To further improve the SMM, this paper further extends the algorithm to support hierarchical B frame structure and bidirectional or multidirectional motion estimation and, moreover, provides the corresponding rate distortion optimized estimation. Several simulation results are presented to verify the improvements of this extension.

This paper describes the implementation of a 3D VR system for real time visual representation and manipulation of data in air traffic management and control. The system has been designed and implemented in collaboration with experts in the Eurocontrol Centre for research and development in air traffic control and is currently undergoing evaluation by air traffic control staff. The system will enable us to determine what benefit, in terms of enhanced understanding and clarity of perception, such 3D displays, combined with enhanced information presentation, can provide to the controller. It is hoped that improvements in this area will permit more efficient and safe management of more aircraft over a wider airspace. Interaction schemes have initially been centred around the use of 3D interactors such as a 3D pointer but we have recently implemented a scheme for voice recognition which allows the user access to a much wider range of commands and actions without recourse to a static keyboard or complex button combinations. The exploitation of carefully selected voice controls frees the user to work within the VR environment using little or no hand-based interaction. We intend to continue development of this system and expect that it will form an evaluation test bed for a wide range of new VR, 3D and other interaction technologies within this application area in the future.

This paper describes an image recognition system designed to inspect the standards quality of electronic assemblies. The essence of the present algorithm is the location of electronics components, at the input image, that disrupt the acceptance requirements for the manufacture of printed circuit board assemblies, which have been adopted by association connecting electronics industries. To this end, image processing modules, based on a nonlinear composite filter are employed with the objective to discriminate between the electronics components that meet the acceptance condition and those that are in defect condition. The proposed recognition system is based on nonlinear composite filter, which is obtained from a training set of reference images. Then, the optimal filter is used in a digital correlator, which results in a simple and robust inspection system.

Extracting minutia and other features from fingerprint images is one of the most important steps in automatic fingerprint identification and classification. This paper proposes a method for the generation of long and secure code that may be used for multi-purpose applications, such as ATM, coded door locks and other security measures. The method consists of two phases; the first phase is carried out using fingerprint image enhancement and thinning. The second phase consists of extracting minutia, ridge ending, bifurcation and all other features in order to produce initial pattern. Finally the multipurposes secure code is generated by applying the one-way MD5 hash function on that pattern. The achieved results are discussed for security improvement. The proposed technique also shows considerable improvement in the minutia detection process in terms of both efficiency and speed.

In this paper, a computer vision system, according to digital image processing methods to recognize car license plate is described. Traffic images are captured by a video camera and digitized in to a computer. Vertical and horizontal line scanning is used. The gray scale in horizontal and vertical lines and a treshold help to find the coordinate of the plate.

Abstract: In this paper a method for classifying cracks in asphalt road by using multi layer Perceptron (MLP) neural network is proposed. Training data are road images which are taken from road surface in 30 degree. The RGB images are first changed to gray scale ...

This paper offers an account of the word order of wh-questions in Omani Arabic as they occur in simple and long-distance questions. In simple questions, the word order of the Inflectional Phrase (IP) varies between Object Verb Subject (OVS) and Verb Object Subject (VOS) as examples (1) and (2) below illustrate. In OVS order, the object referring to the wh-word is expectedly fronted and the order of the subject and verb accords with one of the word order variations exhibited elsewhere in the language. However, VOS word order is peculiar to simple whquestions since it is not attested in affmnative sentences. Ahmed. What did Ahmed eat? Conversely, wh-words impose a unitary SVO word order when they occur in long-distance questions. Example (3) shows that the trace t which sYntactically functions as the object to the verb [kal] 'ate' is preceded by an SV word order. Such a restriction to only SVO is examined in light of Radford's (1997) adverb constituency test and explored in relation to the ECP (Chomsky 1981). In explaining this order, I will also adopt some version of the Lexical Clause Hypothesis (Fukui & Speas 1986). This hypothesis stipulates that subjects can originate inside a lexical projection, usually within VP. They don't have to move to a position higher in the tree.

Varoluşçu aşkın felsefî temellerine bakıldığında, "aşk"ın Cahit Sıtkı Tarancı"nın varoluşunu tamamlayan önemli olgulardan biri olduğu görülecektir. Sokrates"in "Kendini tanı" ve Sartre"ın "Kendini yarat" felsefi görüşleri ışığında şiirleri irdelendiğinde, aşkın Cahit Sıtkı"nın hayatında olmamasının büyük bir eksikliğe yol açacağı görülecektir. O, aşkı yalnızlık ve mutsuzluğu giderecek en büyük ilaç olarak algılar. Egzistansiyalizm"e göre, farklı varlıkların aynı öze ulaşmasında aşk en önemli vasıtalardan biridir. İslam tasavvufundaki aşkın özü de temelde bu anlayışa dayanır. Evrenin yaradılışının temelini aşka bağlayan bir düşüncenin Cahit Sıtkı"nın şiirlerindeki düşünceyle paralellik arz ettiğini belirtmek gerekir. Bu da onun kurguladığı şiirlerine derinlik kazandırmayı amaçladığını gösterir. Modern dünyada nesnelleştirilen aşkın varoluşçu felsefede sevgilide yok olma gibi tasavvufî bir görünümle paralellik arz ettiği de gözden ırak tutulmamalıdır. Cahit Sıtkı Tarancı, şiirlerinde hayat sergüzeştinin ancak aşk duygusuyla anlamlı olabileceğini, aşksızlığın insanı her dem eksik ve mutsuz kılacağını dile getirir. Cahit Sıtkı"yı "ölüm"den uzaklaştırıp, "yaşam"ın kıyısına götüren arzunun temelinde de aşk vardır.

Shearography is a full-field speckle interferometric technique used to determine surface displacement derivatives. For an interferometric technique, shearography is particularly resilient to environmental disturbances and has hence become an invaluable measurement tool outside of the optics laboratory. Furthermore, the inclusion of additional measurement channels has turned shearography from a qualitative inspection tool into a system suitable for quantitative surface strain measurement. In this review article we present a comprehensive overview of the technique, describing the principle of operation, optical configurations, image processing algorithms and applications, with a focus on more recent technological advances.

Background: Studies into the effects of salbutamol in the treatment of wheeze in infancy have been conflicting, possibly due to differences in outcome variables. We aimed to assess the response to salbutamol using indices derived from passive and forced expiration. Methods: We recruited 39 infants who had a history of wheezing (mean age 43 weeks) and measured maximum flow at functional residual capacity (V 0 max FRC ) by rapid thoracoabdominal compression (RTC), and forced expired volume at 0.4 s (FEV 0.4 ) using the raised-volume RTC technique (RV-RTC). We calculated passive compliance (C rs ), resistance (R rs ) and time constant (t) from relaxed expirations that followed the augmented inspirations delivered during RV-RTC. Measurements were repeated after aerosol salbutamol (800 mcg). Results: Data were obtained in 32 infants for V 0 max FRC ; 22 for FEV 0.4 and 19 for passive mechanics. There were no mean changes in any index of forced expiration after salbutamol. Some individuals showed significant changes (improvement or worsening) in one or other index. Overall, there was a small increase in C rs after salbutamol but no change in R rs or t: Conclusions: We found no consistent pattern of response in either index of forced expiration. Validated clinical scores or alternative physiological techniques may be preferable to respiratory mechanics in assessing bronchodilator response.

Fluorescence lifetime imaging (FLIM) is widely applied to obtain quantitative information from fluorescence signals, particularly using Fo ¨rster Resonant Energy Transfer (FRET) measurements to map, for example, protein-protein interactions. Extracting FRET efficiencies or population fractions typically entails fitting data to complex fluorescence decay models but such experiments are frequently photon constrained, particularly for live cell or in vivo imaging, and this leads to unacceptable errors when analysing data on a pixel-wise basis. Lifetimes and population fractions may, however, be more robustly extracted using global analysis to simultaneously fit the fluorescence decay data of all pixels in an image or dataset to a multi-exponential model under the assumption that the lifetime components are invariant across the image (dataset). This approach is often considered to be prohibitively slow and/or computationally expensive but we present here a computationally efficient global analysis algorithm for the analysis of time-correlated single photon counting (TCSPC) or time-gated FLIM data based on variable projection. It makes efficient use of both computer processor and memory resources, requiring less than a minute to analyse time series and multiwell plate datasets with hundreds of FLIM images on standard personal computers. This lifetime analysis takes account of repetitive excitation, including fluorescence photons excited by earlier pulses contributing to the fit, and is able to accommodate time-varying backgrounds and instrument response functions. We demonstrate that this global approach allows us to readily fit time-resolved fluorescence data to complex models including a four-exponential model of a FRET system, for which the FRET efficiencies of the two species of a bi-exponential donor are linked, and polarisation-resolved lifetime data, where a fluorescence intensity and bi-exponential anisotropy decay model is applied to the analysis of live cell homo-FRET data. A software package implementing this algorithm, FLIMfit, is available under an open source licence through the Open Microscopy Environment.

Capabilities of a microwave imaging system working in the air by using two crossed linear arrays are described. The analytic expressions of the focalization procedures are derived and resolution and available volume of reconstruction are discussed. Finally, some experimental images corresponding to two dielectric objects are also shown.

Microscopic deformation analysis has been performed using digital image correlation and artificial neural networks (ANNs). Crosscorrelations of small image regions before and after deformation contain a peak, the position of which indicates the displacement to pixel accuracy. Subpixel resolution has been achieved here by nonintegral pixel shifting and by training ANNs to estimate the fractional part of the displacement. Results from displaced and thermally stressed microelectronic devices indicate these techniques can achieve comparable accuracies to other subpixel techniques and that the use of ANNs can facilitate very fast analysis without knowledge of the analytical form of the image correlation function.

Image processing is a mechanism to convert an image into digital form and perform various operations on it, in order to get an enhanced image or to extract some useful information from it. In Image processing system, it treats images as two dimensional signals while applying number of image processing methods to them. This leads to an increasing number of generated digital images. Therefore it is required automatic systems to recognize the objects from the images. These systems may collect the number of features of a image and specification of image and consequently the different features of an object will identify the object from the image. Image processing is among rapidly growing technologies today, with its applications in various aspects of a business. Image Processing forms core research area within engineering and computer science disciplines too. Its most common and effective method is retrieve the textual features from various methods. But most of the methods do not yield the more accurate features form the image. So there is a requirement of an effective and efficient method for features extraction from the image. Moreover, images are rich in content, so some approaches are proposed based on various features derived directly from the content of the image: these are the grid-based-color-moments (GBCM) approaches. They allow users to search the desired object from image by specifying visual features (e.g., colour, texture and shape). Once the features have been defined and extracted, the retrieval becomes a task of measuring similarity between image features. In this paper, we have proposed a number of existing methods for GBCM applications.

Safe offshore operations and navigation in Arctic water requires reliable surveillance of icebergs. Synthetic Aperture Radar (SAR) is widely used by governments and industry to monitor iceberg locations in ice frequented waters. One of the primary challenges in using SAR data for this application is the discrimination of vessel targets from icebergs. In the context of iceberg surveillance, vessel targets are considered false alarms and the same is true of icebergs in vessel monitoring applications. The present state of the art in SAR-based vessel and iceberg discrimination is the use of machine learning to train algorithms to distinguish between vessel and iceberg backscatter. Machine learning requires the use of large datasets of validated iceberg and vessel targets, which can be costly and time consuming to collect. One solution to the problem is the use of a physical-based electromagnetic (EM) backscatter modelling of iceberg and ship targets in SAR data. The availability of such...

The present work deals with the recognition of Indian postal letter sorting system based on PIN code. The optical camera catches the front and back view of each postal letter at a time. The vision system ensures from address and to address along with postal department stamp, seal etc., In this paper, an attempt has been made to recognize PIN codes by using Connected Component (CC) approach, Artificial Neural Networks (ANN) and Barcode approaches. The six nearest neighbour CCs technique instead of 4 or 8 CCs has been adopted to recognize handwritten numerals. The ANN classifier technique has been used to recognize the numerals in the PIN code. In this paper, the development of exact barcode to each PIN code is introduced for sorting the postal letters automatically. The letters travel up to barcode scanner, if the PIN code is written on the envelope, equivalent barcodes are developed and printed on the each of the postal letters in the bottom line by the barcode printer, if PIN codes are not written on the envelope, by comparing a lookup table of place and PIN code, equivalent barcode to PIN code will be printed on the bottom of the postal letter. Then the automatic letter sorting system is employed to sort the letters using the barcodes. The conveyor belt which is having gates at each check points works on the basis of on/off condition, enables the letter to travel up to exact location of the destination box. A comparative study has been made for the above approaches and the results are displayed. The experiments were performed on automatic postal letter sorting machine which is situated near to Meenambakkam Airport, Chennai. The experimental results reveal that barcode approach yields 99.5% of accuracy.

design, weight and so on. Hence, it is easy for the automatic machine to classify Indian coins.. There are many coin classification machines are available, but , the machine has to be designed for recognition of Indian coin. To increase the efficiency of the machine, they are to be embedded with proper source code.In this paper, Sobel Filter, HA and HT are used to classify the coin image. It is proposed a method for realizing a simple automatic coin recognition system more effectively. The HT technique is used to recognize almost 100% of the coin image. Comparing to Sobel edge detection method, HA the HT gives better result.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

We present the XMM-Newton first light image, taken in January 2000 with the EPIC pn camera during the instrument's commissioning phase, when XMM-Newton was pointing towards the Large Magellanic Cloud (LMC). The field is rich in different kinds of X-ray sources: point sources, supernova remnants (SNRs) and diffuse X-ray emission from LMC interstellar gas. The observations are of unprecedented sensitivity, reaching a few 10 32 erg/s for point sources in the LMC. We describe how these data sets were analysed and discuss some of the spectroscopic results. For the SNR N157B the power law spectrum is clearly steeper than previously determined from ROSAT and ASCA data. The existence of a significant thermal component is evident and suggests that N157B is not a Crab-like but a composite SNR. Most puzzling is the spectrum of the LMC hot interstellar medium, which indicates a significant overabundance of Ne and Mg of a few times solar.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

This paper focuses on the minimization of the time of the dominant straight line detection in an image using Hough Transform algorithm. The idea is a mixture between two domains, namely image processing and multi-agent systems. The importance of this work comes from the relying of image processing techniques on hardware accelerations. This paper demonstrates how the distribution of a purely sequential processing on a set of agents leads to an improvement from time execution point of view. The purpose is to reduce the execution time of Hough transform technique through the distribution of the algorithm on a set of reactive agents. This may allow the exploitation of a parallel or distributed environment. The main idea is based on the division of similar repeated processing with different parameters on several agents. It is a SIMD-like architecture according to Flynn classification. The obtained results are promising in the way that the execution time is at least divided by 4 comparatively to the use of the algorithm in its sequential form.

This study emphasizes the importance of energy-aware Techniques for processing image algorithms in the Internet of Things (IoT) to create secure IoT and energy efficiency. IoT-systems dependent (IoTSs) consume a significant amount of energy. This ranks as one of the most serious challenges linked with IoTSs. Another challenge is that digital asset protection is a significant task and complexity. The processing of images has lately played a critical role in tackling these challenges, As outlined in this article. Proposed techniques are developed daily, so IoT deployment is now clearly integrated into our daily activities. Several effective image-processing algorithms for IoTSs to address such difficulties have been developed. This study examines processing for image algorithms used by various kinds of IoTSs. The novel contribution is to offer viewers an illustration of appropriate Techniques for processing image algorithms for usage with specific sorts of IoT systems. Both analysis and discussion have produced showing some possible solutions (Techniques for processing image algorithms) that might be useful in the development of an intelligent IoT system that is secure, and energy-efficient.

Rotating machines and reciprocating machines like turbines, combustion engines and electric motor are the most widely used in industry. These machine consist of components which generate vibration dan heat during operation. Excessive vibration and heat can be indicators of fault in the machine. Therefore, machine condition monitoring is needed to monitor the real time machine condition with proper devices and methods. One of those being developed now is using infrared thermography. This method is categorized in the ...

This paper presents a human action recognition method using dynamic time warping and voting algorithms on 3D human skeletal models. In this method human actions, which are the combinations of multiple body part movements, are described by feature matrices concerning both spatial and temporal domains. The feature matrices are created based on the spatial selection of relative angles between body parts in time series. Then, action recognition is done by applying a classifier which is the combination of dynamic time warping (DTW) and a voting algorithm to the feature matrices. Experimental results show that the performance of our action recognition method obtains high recognition accuracy at reliable computation speed and can be applied in real time human action recognition systems.

Additive manufacturing (AM) is an essential tool to make 3D objects having very complex shapes and geometries, unachievable with standard manufacturing approaches. Meanwhile, quality controls of such objects become challenging for both industrials and applications in laboratories due to both their complexity and the materials they are made of. Consequently, we demonstrate that terahertz (THz) imaging and THz tomography can be considered as efficient methods for such object inspection in routine applications. Thus, this paper proposes an experimental study of 3D polymer objects obtained by AM techniques. This approach allows us to characterize defects and to control dimensions by volumetric measurements on 3D data reconstructed by tomography.

In this paper, we present an advanced image processing sequence to perform nondestructive inspection from 3-D terahertz (THz) images. We develop all the steps starting from a 3-D tomographic reconstruction of a sample from radiographs acquired with a monochromatic millimeter-wave imaging system to an automated segmentation, extracting the different volumes of interest (VOI) composing the sample. This leads to 3-D visualization and dimensional measurements. This inspection is completed by a skeletonization and caliber analysis providing an accurate assessment of the structure, geometry, and morphology of the acquired object. Overall sequence is implemented onto an unique software and validated through different sample analysis.

We investigate in this paper a new reconstruction method in order to perform 3D Terahertz (THz) tomography using a continuous wave acquisition setup in transmission mode. This method is based on the Maximum Likelihood for TRansmission tomography (ML-TR) first developed for X-ray imaging. We optimize the Ordered Subsets Convex (OSC) implementation of the ML-TR by including the Gaussian propagation model of THz waves and take into account the intensity distributions of both blank calibration scan and dark-field measured on THz detectors. THz ML-TR reconstruction quality and accuracy are discussed and compared to other tomographic reconstructions.

In this paper, a model of the beam propagation is developed according to the physical properties of THz waves used in THz computed tomography (CT) scan imaging. This model is first included in an acquisition simulator to observe and estimate the impact of the Gaussian beam intensity profile on the projection sets. Second, the model is introduced in several inversion methods as a convolution filter to perform efficient tomographic reconstructions of simulated and real acquired objects. Results obtained with three reconstruction methods (BFP, SART and OSEM) are compared to the techniques proposed in this paper. We focus our discussion on the efficiency of optimized algorithms to increase the overall quality and accuracy of the reconstructions.

terahertz computed tomography has already been performed with three different reconstruction methods (standard back-projection algorithm and two iterative analyses) to reconstruct 3-D objects. A Gaussian beam model is developed according to the physical properties of terahertz waves such as the energy distribution within the propagation path. This model is included as a new convolution filter into the tomographic reconstruction methods in order to analyze the impact of a such effect and then to enhance quality and accuracy of the resulting images. We demonstrate the improvements of the optimized reconstructions for applied 3-D terahertz tomography.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

We report on the first results of an imaging survey to detect strong gravitational lensing targeting the richest clusters selected from the photometric data of the Sloan Digital Sky Survey (SDSS) with follow-up deep imaging observations from the Wisconsin Indiana Yale NOAO (WIYN) 3.5m telescope and the University of Hawaii 88-inch telescope (UH88). The clusters are selected from an area of 8000 deg 2 using the Red Cluster Sequence technique and span the redshift range 0.1 z 0.6, corresponding to a comoving cosmological volume of ∼ 2Gpc 3 . Our imaging survey thus targets a volume more than an order of magnitude larger than any previous search. A total of 240 clusters were imaged of which 141 had sub-arcsecond image quality. Our survey has uncovered 16 new lensing clusters with definite giant arcs, an additional 12 systems for which the lensing interpretation is very likely, and 9 possible lenses which contain shorter arclets or candidate arcs which are less certain and will require further observations to confirm their lensing origin. The number of new cluster lenses detected in this survey is likely 30. Among these new systems are several of the most dramatic examples of strong gravitational lensing ever discovered with multiple bright arcs at large angular separation. These will likely become 'poster-child' gravitational lenses similar to Abell 1689 and CL0024+1654. The new lenses discovered in this survey will enable future sysetmatic studies of the statistics of strong lensing and its implications for cosmology and our structure formation paradigm.

Over the last decade, smartphones have changed radically to support us with mHealth technology, cloud computing, and machine learning algorithm. Having its multifaceted facilities, we present a novel smartphone-based noninvasive hemoglobin (Hb) level prediction model by analyzing hue, saturation and value (HSV) of a fingertip video. Here, we collect 60 videos of 60 subjects from two different locations: Blood Center of Wisconsin, USA and AmaderGram, Bangladesh. We extract red, green, and blue (RGB) pixel intensities of selected images of those videos captured by the smartphone camera with flash on. Then we convert RGB values of selected video frames of a fingertip video into HSV color space and we generate histogram values of these HSV pixel intensities. We average these histogram values of a fingertip video and consider as an observation against the gold standard Hb concentration. We generate two input feature matrices based on observation of two different data sets. Partial Least ...

We introduce a two-step iterative segmentation and registration method to find coplanar surfaces among stereo images of a polyhedral environment. The novelties of this paper are: (i) to propose a user-defined initialization easing the image matching and segmentation, (ii) to incorporate color appearance and planar projection information into a Bayesian segmentation scheme, and (iii) to add consistency to the projective transformations related to the polyhedral structure of the scenes. The method utilizes an assisted Bayesian color segmentation scheme. The initial user-assisted segmentation is used to define search regions for planar homography image registering. The two reliable methods cooperate together to obtain probabilities for coplanar regions with similar color information that are used to get a new segmentation by means of Quadratic Markov Measure Fields (QMMF). We search for the best regions by iterating both steps: registration and segmentation.

We present a generic regularized formulation, based on robust half-quadratic regularization, for unwrapping noisy and discontinuous wrapped phase maps. Two cases are presented: the convex and the non-convex one. The unwrapped phase with the convex formulation is unique and robust to noise; however, the convex function solution is deteriorated by real discontinuities in phase maps; therefore, we also present a non-convex formulation which, with a parameter continuation strategy, shows a superior performance.

We propose a robust method for computing discontinuous phase maps from fringe pattern with carrier frequency. Our algorithm is based on the minimization of an edgepreserving regularized cost functional, specifically, on a robust regularized potential which uses the Plate with Adaptive Rest Condition paradigm (PARC), i.e. a second order edge preserving potential. Given that the proposed cost function is no-convex, our method uses as initial point an over smoothed phase computed with a standard fringe analysis method and then reconstructs the phase discontinuities. Although the method is for general purpose, it is introduced in the context of interferometric Gauge Blocks calibration. The performance of the algorithm is demonstrated by numerical experiments with both synthetic and real data. © Optical Society of America (OSA)

A powerful technique for processing fringe-pattern images is based on Bayesian estimation theory with prior Markov random-field models. In this approach the solution of a processing problem is characterized as the minimizer of a cost function with terms that specify that the solution should be compatible with the available observations and terms that impose certain ͑prior͒ constraints on the solution. We show that, by the appropriate choice of these terms, one can use this approach in almost every processing step for accurate and robust interferogram demodulation and phase unwrapping.

We present a modification of the multigrid method for the minimization of quadratic cost functions that result from the formulation of several problems in the digital processing of fringe-pattern images by using the Bayesian estimation-theory framework. With this modification the method can be applied to irregular domains and results in substantial savings in computational cost. We compare it with other state-of-the-art numerical techniques and present examples of its application to image smoothing without edge effects, robust quadrature filtering for the phase demodulation of spatial-carrier fringe patterns, and robust phase unwrapping.

The biometric person authentication technique based on the pattern of the human iris is well suited to be applied to any access control system requiring a high level of security. Iris recognition is a proven, accurate means to identify people. Iris recognition system includes the preprocessing system, segmentation, features extraction and recognition. Especially we focus on image segmentation and statistical feature extraction for iris recognition process. The iris recognition system is highly depending on segmentation. A good number of identification systems based on behavioral characteristics (such as voice, handwriting, signature, speech, and keystroke) and physical characteristics (such as face, finger print iris etc) are being employed for identification of an individual. A compare has been made between these two techniques using FAR analysis, FRR analysis, memory requirement and algorithmic complexity.

Agricultural productivity is significantly impacted by leaf diseases, which can lead to large economic losses. Common methods of disease identification and pesticide selection rely heavily on manual inspection and expert knowledge, making them timeconsuming and prone to errors. This paper presents an automated system for detecting plant leaf diseases and recommending appropriate pesticides using image processing and machine learning techniques. The proposed system captures leaf images, processes them using deep learning algorithms to identify diseases, and then suggests optimal pesticides based on an expert database. By leveraging artificial intelligence, this approach enhances accuracy, reduces dependency on human expertise, and promotes timely intervention, ultimately improving crop yield and sustainability. Experimental results demonstrate the effectiveness of the model in identifying common plant diseases with high accuracy and providing precise pesticide recommendations. This system holds high potential for integration into smart farming solutions, offering a scalable and costeffective tool for farmers worldwide.

Since a Grid-connected photovoltaic system is expensive to build and the cost of electricity from the PV array systems is more expensive, compared to the price of electricity from the utility grid, the user of such system naturally wants to use all of the availble output power. Therefore, PV array systems should be designed to operate at their maximum output power levels for any temperature and solar irradiation level at all time. To obtain maximum power from photovoltaic array, photovoltaic power system usally requires maximum power point tracking controller. This project proposes maximum power point tracking control of photovoltaic array uzing fuzzy control. To obtain maximum power from photovoltaic array, the fuzzy controller only uses the output power. Therfore this method can track maximum power point rapidly with fuzzy inference even if the optimum operating point changes.

A hallmark feature of cognitive aging is a decline in the ability to form new memories. Parallel to these cognitive impairments are marked disruptions in sleep physiology. Despite recent evidence in young adults establishing a role for sleep spindles in restoring hippocampal-dependent memory formation, the possibility that disrupted sleep physiology contributes to age-related decline in hippocampaldependent learning remains unknown. Here, we demonstrate that reduced prefrontal sleep spindles by over 40% in older adults statistically mediates the effects of old age on next day episodic learning, such that the degree of impaired episodic learning is explained by the extent of impoverished prefrontal sleep spindles. In addition, prefrontal spindles significantly predicted the magnitude of impaired next day hippocampal activation, thereby determining the influence of spindles on post-sleep learning capacity. These data support the hypothesis that disrupted sleep physiology contributes to age-related cognitive decline in later life, the consequence of which has significant treatment intervention potential.

This paper describes the Classification of bulk OCT retinal fundus images of normal and diabetic retinopathy using the Intensity histogram features, Gray Level Co-Occurrence Matrix (GLCM), and the Gray Level Run Length Matrix (GLRLM) feature extraction techniques. Three features-Intensity histogram features, GLCM, and GLRLM were taken and, that features were compared fairly. A total of 301 bulk OCT retinal fundus color images were taken for two different varieties which are normal and diabetic retinopathy. For classification and feature extraction, a filtered image output based on a fourth-order PDE is used. Using OCT retinal fundus images, the most effective feature extraction method is identified.

In this paper we present a robust real-time method for tracking and recognizing multiple people with multiple cameras. Our method uses both static and Pan-Tilt-Zoom (PTZ) cameras to provide visual attention. The PTZ camera system uses face recognition to register people in the scene and``lock-on''to those individuals. The static camera system provides a global view of the environment and is used to re-adjust the tracking of the system when the PTZ cameras lose their targets. The system works well even when people ...

La détermination du profil hydrique dans le bois au cours du temps permet de comprendre et de prédire les phénomènes liés au séchage, le comportement mécanique du bois, et les risques d'attaques fongiques. En effet ces quelques pourcentages d'eau situés au sein des parois cellulaires vont avoir une forte influence notamment sur les caractéristiques mécaniques de celles-ci. Aujourd'hui l'Eurocode 5 propose un abaque d'équilibre hygroscopique unique, basé sur le séchage de résineux uniquement. Nous proposons de référencer les phénomènes physiques mis en jeu lors du transfert hydrique dans un élément en bois soumis à un environnement variable en humidité et température, afin de d'identifier des propriétés de diffusion des essences de bois. De nouveaux abaques d'équilibre hygroscopique pour les essences de feuillus sont proposés en vue d'une meilleure valorisation de ces derniers dans la construction. MOTS-CLÉS : abaque d'équilibre hygroscopique, couplage thermo-hydrique, hygroscopique, feuillus, paramètres de diffusion