Search results for: texture reconstruction

Authors: Wajdi Bellil, Chokri Ben Amar, Adel M. Alimi

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An application of Beta wavelet networks to synthesize pass-high and pass-low wavelet filters is investigated in this work. A Beta wavelet network is constructed using a parametric function called Beta function in order to resolve some nonlinear approximation problem. We combine the filter design theory with wavelet network approximation to synthesize perfect filter reconstruction. The order filter is given by the number of neurons in the hidden layer of the neural network. In this paper we use only the first derivative of Beta function to illustrate the proposed design procedures and exhibit its performance.

Keywords: Beta wavelets, Wavenet, multiresolution analysis, perfect filter reconstruction, salient point detect, repeatability.

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Authors: A. Özyer, N. G. Turan, Y. Ardalı

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The environmental fate of organic contaminants in soils is influenced significantly by the pH, texture of soil, water content and also presence of organic matter. In this study, biodegradation of endosulfan isomers was studied in two different soils (Soil A and Soil B) that have contrasting properties in terms of their texture, pH, organic content, etc. Two Nocardia sp., which were isolated from soil, were used for degradation of endosulfan. Soils were contaminated with commercial endosulfan. Six sets were maintained from two different soils, contaminated with different endosulfan concentrations for degradation experiments. Inoculated and uninoculated mineral media with Nocardia isolates were added to the soils and mixed. Soils were incubated at a certain temperature (30 °C) during ten weeks. Residue endosulfan and its metabolites’ concentrations were determined weekly during the incubation period. The changes of the soil microorganisms were investigated weekly.

Keywords: Endosulfan, biodegradation, Nocardia sp., soil, organochlorine pesticide.

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Authors: Stoyan Nedeltchev, Markus Schubert

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By means of the ultrafast X-ray tomography facility, data were obtained at different superficial gas velocities U_G in a bubble column (0.1 m in ID) operated with an air-deionized water system at ambient conditions. Raw reconstructed images were treated by both the information entropy (IE) and the reconstruction entropy (RE) algorithms in order to identify the main transition velocities in a bubble column. The IE values exhibited two well-pronounced minima at U_G=0.025 m/s and U_G=0.085 m/s identifying the boundaries of the homogeneous, transition and heterogeneous regimes. The RE extracted from the central region of the column’s cross-section exhibited only one characteristic peak at U_G=0.03 m/s, which was attributed to the transition from the homogeneous to the heterogeneous flow regime. This result implies that the transition regime is non-existent in the core of the column.

Keywords: Bubble column, ultrafast X-ray tomography, information entropy, reconstruction entropy.

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Authors: Awais Adnan, Muhammad Nawaz, Sajid Anwar, Tamleek Ali, Muhammad Ali

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Needs of an efficient information retrieval in recent years in increased more then ever because of the frequent use of digital information in our life. We see a lot of work in the area of textual information but in multimedia information, we cannot find much progress. In text based information, new technology of data mining and data marts are now in working that were started from the basic concept of database some where in 1960. In image search and especially in image identification, computerized system at very initial stages. Even in the area of image search we cannot see much progress as in the case of text based search techniques. One main reason for this is the wide spread roots of image search where many area like artificial intelligence, statistics, image processing, pattern recognition play their role. Even human psychology and perception and cultural diversity also have their share for the design of a good and efficient image recognition and retrieval system. A new object based search technique is presented in this paper where object in the image are identified on the basis of their geometrical shapes and other features like color and texture where object-co-relation augments this search process. To be more focused on objects identification, simple images are selected for the work to reduce the role of segmentation in overall process however same technique can also be applied for other images.

Keywords: Object correlation, Geometrical shape, Color, texture, features, contents.

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Authors: Ssu-Han Chen, Der-Baau Perng

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Molding process in IC manufacturing secures chips against the harms done by hot, moisture or other external forces. While a chip was being molded,defects like cracks, dilapidation, or voids may be embedding on the molding surface. The molding surfaces the study poises to treat and the ones on the market, though, differ in the surface where texture similar to defects is everywhere. Manual inspection usually passes over low-contrast cracks or voids; hence an automatic optical inspection system for molding surface is necessary. The proposed system is consisted of a CCD, a coaxial light, a back light as well as a motion control unit. Based on the property of statistical textures of the molding surface, a series of digital image processing and classification procedure is carried out. After training of the parameter associated with above algorithm, result of the experiment suggests that the accuracy rate is up to 93.75%, contributing to the inspection quality of IC molding surface.

Keywords: Molding surface, machine vision, statistical texture, discrete Fourier transformation.

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Authors: H. B. Kekre, Kavita Patil

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This paper describes a novel and effective approach to content-based image retrieval (CBIR) that represents each image in the database by a vector of feature values called “Standard deviation of mean vectors of color distribution of rows and columns of images for CBIR". In many areas of commerce, government, academia, and hospitals, large collections of digital images are being created. This paper describes the approach that uses contents as feature vector for retrieval of similar images. There are several classes of features that are used to specify queries: colour, texture, shape, spatial layout. Colour features are often easily obtained directly from the pixel intensities. In this paper feature extraction is done for the texture descriptor that is 'variance' and 'Variance of Variances'. First standard deviation of each row and column mean is calculated for R, G, and B planes. These six values are obtained for one image which acts as a feature vector. Secondly we calculate variance of the row and column of R, G and B planes of an image. Then six standard deviations of these variance sequences are calculated to form a feature vector of dimension six. We applied our approach to a database of 300 BMP images. We have determined the capability of automatic indexing by analyzing image content: color and texture as features and by applying a similarity measure Euclidean distance.

Keywords: Standard deviation Image retrieval, color distribution, Variance, Variance of Variance, Euclidean distance.

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Authors: A. Borji, M. Hamidi

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In this paper we examine the use of global texture analysis based approaches for the purpose of Persian font recognition in machine-printed document images. Most existing methods for font recognition make use of local typographical features and connected component analysis. However derivation of such features is not an easy task. Gabor filters are appropriate tools for texture analysis and are motivated by human visual system. Here we consider document images as textures and use Gabor filter responses for identifying the fonts. The method is content independent and involves no local feature analysis. Two different classifiers Weighted Euclidean Distance and SVM are used for the purpose of classification. Experiments on seven different type faces and four font styles show average accuracy of 85% with WED and 82% with SVM classifier over typefaces

Keywords: Persian font recognition, support vector machine, gabor filter.

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Authors: A. Ghodbane, M. Saad, J.-F. Boland, C. Thibeault

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Historically, actuators’ redundancy was used to deal with faults occurring suddenly in flight systems. This technique was generally expensive, time consuming and involves increased weight and space in the system. Therefore, nowadays, the on-line fault diagnosis of actuators and accommodation plays a major role in the design of avionic systems. These approaches, known as Fault Tolerant Flight Control systems (FTFCs) are able to adapt to such sudden faults while keeping avionics systems lighter and less expensive. In this paper, a (FTFC) system based on the Geometric Approach and a Reconfigurable Flight Control (RFC) are presented. The Geometric approach is used for cosmic ray fault reconstruction, while Sliding Mode Control (SMC) based on Lyapunov stability theory is designed for the reconfiguration of the controller in order to compensate the fault effect. Matlab®/Simulink® simulations are performed to illustrate the effectiveness and robustness of the proposed flight control system against actuators’ faulty signal caused by cosmic rays. The results demonstrate the successful real-time implementation of the proposed FTFC system on a non-linear 6 DOF aircraft model.

Keywords: Actuators’ faults, Fault detection and diagnosis, Fault tolerant flight control, Sliding mode control, Geometric approach for fault reconstruction, Lyapunov stability.

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Authors: R. Moosazadeh

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From ancient times, in some cultures, the way of choosing the colour and pattern of the fabric, and its decoration, represents a message about their beliefs, traditions and ethnical origins. Due to the diversity of clothing in the Middle East, two special types of Iranian fabrics have been investigated. The process of knitting with a weaving-loom is always accompanied by passing the fibres of the warp in different ways. This study presented the historical investigation of brocades and explanation about traditional Iranian brocades in terms of fabric, shape, and patterns. Moreover, the compression results between characteristics of Termeh and velvet have been reported. The aim of the study was to focus on the history of fabric texture in Iran and general information about brocades and Termeh fabrics in expressions of their historical traditions. In conclusion, it is attempted to introduce knitting techniques and designed models which have been presented for this traditional and expensive Iranian fabric.

Keywords: Texture, brocade, Termeh, Velvet Braid.

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Authors: Ahadollah Azami, Alireza Sadeghi, Zargham OstadiAsl, Hamed Pirjani, Milad Babaei

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Stairway Ushtobin Village is one of the five villages with original and sustainable architecture in Northwest of Iran along the border of Armenia, which has been able to maintain its environment and sustainable ecosystem. Studying circulation, function and scale (grand, medium and minor) of space, ratio of full and empty spaces, number and height of stairs, ratio of compound volume to luxury spaces, openings, type of local masonry (stone, mud, wood) and form of covering elements have been carried out in four houses of this village comparatively as some samples in this article, and furthermore, this article analyzes that the architectural shapes and organic texture of the village meet the needs of cold and dry climate. Finally, some efficient plans are offered suiting the present needs of the village to have a sustainable architecture.

Keywords: Sustainable Architecture, Local Materials, Village Texture, Form, Skeleton

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Authors: Bremananth R., Veerabadran C. S., Andy W. H. Khong

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Automatic reading of handwritten cheque is a computationally complex process and it plays an important role in financial risk management. Machine vision and learning provide a viable solution to this problem. Research effort has mostly been focused on recognizing diverse pitches of cheques and demand drafts with an identical outline. However most of these methods employ templatematching to localize the pitches and such schemes could potentially fail when applied to different types of outline maintained by the bank. In this paper, the so-called outline problem is resolved by a cheque information tree (CIT), which generalizes the localizing method to extract active-region-of-entities. In addition, the weight based density plot (WBDP) is performed to isolate text entities and read complete pitches. Recognition is based on texture features using neural classifiers. Legal amount is subsequently recognized by both texture and perceptual features. A post-processing phase is invoked to detect the incorrect readings by Type-2 grammar using the Turing machine. The performance of the proposed system was evaluated using cheque and demand drafts of 22 different banks. The test data consists of a collection of 1540 leafs obtained from 10 different account holders from each bank. Results show that this approach can easily be deployed without significant design amendments.

Keywords: Cheque reading, Connectivity checking, Text localization, Texture analysis, Turing machine, Signature verification.

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Authors: J. L. Liu, L. Wang, B. Zhu, J. Zhou, W. D. Gao

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Fabric textures are very common in our daily life. However, the representation of fabric textures has never been explored from neuroscience view. Theoretical studies suggest that primary visual cortex (V1) uses a sparse code to efficiently represent natural images. However, how the simple cells in V1 encode the artificial textures is still a mystery. So, here we will take fabric texture as stimulus to study the response of independent component analysis that is established to model the receptive field of simple cells in V1. We choose 140 types of fabrics to get the classical fabric textures as materials. Experiment results indicate that the receptive fields of simple cells have obvious selectivity in orientation, frequency and phase when drifting gratings are used to determine their tuning properties. Additionally, the distribution of optimal orientation and frequency shows that the patch size selected from each original fabric image has a significant effect on the frequency selectivity.

Keywords: Fabric Texture, Receptive Filed, Simple Cell, Spare Coding.

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Authors: D. Zare, M. Alirezaei, S.M. Nassiri

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Iran is one of the greatest producers of date in the world. However due to lack of information about its viscoelastic properties, much of the production downgraded during harvesting and postharvesting processes. In this study the effect of temperature and moisture content of product were investigated on stress relaxation characteristics. Therefore, the freshly harvested date (kabkab) at tamar stage were put in controlled environment chamber to obtain different temperature levels (25, 35, 45, and 55 0C) and moisture contents (8.5, 8.7, 9.2, 15.3, 20, 32.2 %d.b.). A texture analyzer TAXT2 (Stable Microsystems, UK) was used to apply uniaxial compression tests. A chamber capable to control temperature was designed and fabricated around the plunger of texture analyzer to control the temperature during the experiment. As a new approach a CCD camera (A4tech, 30 fps) was mounted on a cylindrical glass probe to scan and record contact area between date and disk. Afterwards, pictures were analyzed using image processing toolbox of Matlab software. Individual date fruit was uniaxially compressed at speed of 1 mm/s. The constant strain of 30% of thickness of date was applied to the horizontally oriented fruit. To select a suitable model for describing stress relaxation of date, experimental data were fitted with three famous stress relaxation models including the generalized Maxwell, Nussinovitch, and Pelege. The constant in mentioned model were determined and correlated with temperature and moisture content of product using non-linear regression analysis. It was found that Generalized Maxwell and Nussinovitch models appropriately describe viscoelastic characteristics of date fruits as compared to Peleg mode.

Keywords: Stress relaxation, Viscoelastic properties, Date, Texture analyzer.

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Authors: Dai Zhimei, Hua Chen

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The exploration of urban spatial evolution is an important part of urban development research. Therefore, the evolutionary modern Yangzhou urban spatial texture was taken as the research object, and Spatial Syntax was used as the main research tool, this paper explored Yangzhou spatial evolution law and its driving factors from the urban street network scale, district scale and street scale. The study has concluded that at the urban scale, Yangzhou urban spatial evolution is the result of a variety of causes, including physical and geographical condition, policy and planning factors, and traffic conditions, and the evolution of space also has an impact on social, economic, environmental and cultural factors. At the district and street scales, changes in space will have a profound influence on the history of the city and the activities of people. At the end of the article, the matters needing attention during the evolution of urban space were summarized.

Keywords: Space Syntax, spatial texture, urban space, Yangzhou.

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Authors: Nagesha, G. Hemantha Kumar

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Although the level crossing concept has been the subject of intensive investigation over the last few years, certain problems of great interest remain unsolved. One of these concern is distribution of threshold levels. This paper presents a new threshold level allocation schemes for level crossing based on nonuniform sampling. Intuitively, it is more reasonable if the information rich regions of the signal are sampled finer and those with sparse information are sampled coarser. To achieve this objective, we propose non-linear quantization functions which dynamically assign the number of quantization levels depending on the importance of the given amplitude range. Two new approaches to determine the importance of the given amplitude segment are presented. The proposed methods are based on exponential and logarithmic functions. Various aspects of proposed techniques are discussed and experimentally validated. Its efficacy is investigated by comparison with uniform sampling.

Keywords: speech signals, sampling, signal reconstruction, asynchronousdelta modulation, non-linear quantization.

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Authors: V. Masilamani, Kamala Krithivasan

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We study the problem of reconstructing a three dimensional binary matrices whose interiors are only accessible through few projections. Such question is prominently motivated by the demand in material science for developing tool for reconstruction of crystalline structures from their images obtained by high-resolution transmission electron microscopy. Various approaches have been suggested to reconstruct 3D-object (crystalline structure) by reconstructing slice of the 3D-object. To handle the ill-posedness of the problem, a priori information such as convexity, connectivity and periodicity are used to limit the number of possible solutions. Formally, 3Dobject (crystalline structure) having a priory information is modeled by a class of 3D-binary matrices satisfying a priori information. We consider 3D-binary matrices with periodicity constraints, and we propose a polynomial time algorithm to reconstruct 3D-binary matrices with periodicity constraints from two orthogonal projections.

Keywords: 3D-Binary Matrix Reconstruction, Computed Tomography, Discrete Tomography, Integral Max Flow Problem.

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Authors: Varin Chouvatut, Suthep Madarasmi, Mihran Tuceryan

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This paper aims to propose a novel, robust, and simple method for obtaining a human 3D face model and camera pose (position and orientation) from a video sequence. Given a video sequence of a face recorded from an off-the-shelf digital camera, feature points used to define facial parts are tracked using the Active- Appearance Model (AAM). Then, the face-s 3D structure and camera pose of each video frame can be simultaneously calculated from the obtained point correspondences. This proposed method is primarily based on the combined approaches of Gradient Descent and Powell-s Multidimensional Minimization. Using this proposed method, temporarily occluded point including the case of self-occlusion does not pose a problem. As long as the point correspondences displayed in the video sequence have enough parallax, these missing points can still be reconstructed.

Keywords: Camera Pose, Face Reconstruction, Gradient Descent, Powell's Multidimensional Minimization.

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Authors: Smriti H. Bhandari, S. M. Deshpande

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Surface metrology with image processing is a challenging task having wide applications in industry. Surface roughness can be evaluated using texture classification approach. Important aspect here is appropriate selection of features that characterize the surface. We propose an effective combination of features for multi-scale and multi-directional analysis of engineering surfaces. The features include standard deviation, kurtosis and the Canny edge detector. We apply the method by analyzing the surfaces with Discrete Wavelet Transform (DWT) and Dual-Tree Complex Wavelet Transform (DT-CWT). We used Canberra distance metric for similarity comparison between the surface classes. Our database includes the surface textures manufactured by three machining processes namely Milling, Casting and Shaping. The comparative study shows that DT-CWT outperforms DWT giving correct classification performance of 91.27% with Canberra distance metric.

Keywords: Dual-tree complex wavelet transform, surface metrology, surface roughness, texture classification.

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Authors: K.Mala, V.Sadasivam, S.Alagappan

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Advances in clinical medical imaging have brought about the routine production of vast numbers of medical images that need to be analyzed. As a result an enormous amount of computer vision research effort has been targeted at achieving automated medical image analysis. Computed Tomography (CT) is highly accurate for diagnosing liver tumors. This study aimed to evaluate the potential role of the wavelet and the neural network in the differential diagnosis of liver tumors in CT images. The tumors considered in this study are hepatocellular carcinoma, cholangio carcinoma, hemangeoma and hepatoadenoma. Each suspicious tumor region was automatically extracted from the CT abdominal images and the textural information obtained was used to train the Probabilistic Neural Network (PNN) to classify the tumors. Results obtained were evaluated with the help of radiologists. The system differentiates the tumor with relatively high accuracy and is therefore clinically useful.

Keywords: Fuzzy c means clustering, texture analysis, probabilistic neural network, LVQ neural network.

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Authors: Chung-Hsin Huang, Chien-Ching Chiu, Chun Jen Lin

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The electromagnetic imaging of inhomogeneous dielectric cylinders buried in a slab medium by transverse electric (TE) wave illumination is investigated. Dielectric cylinders of unknown permittivities are buried in second space and scattered a group of unrelated waves incident from first space where the scattered field is recorded. By proper arrangement of the various unrelated incident fields, the difficulties of ill-posedness and nonlinearity are circumvented, and the permittivity distribution can be reconstructed through simple matrix operations. The algorithm is based on the moment method and the unrelated illumination method. Numerical results are given to demonstrate the capability of the inverse algorithm. Good reconstruction is obtained even in the presence of additive Gaussian random noise in measured data. In addition, the effect of noise on the reconstruction result is also investigated.

Keywords: Slab Medium, Unrelated Illumination Method, TEWave Illumination, Inhomogeneous Cylinders.

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Authors: Mounir Ait kerroum, Ahmed Hammouch, Driss Aboutajdine

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Texture information plays increasingly an important role in remotely sensed imagery classification and many pattern recognition applications. However, the selection of relevant textural features to improve this classification accuracy is not a straightforward task. This work investigates the effectiveness of two Mutual Information Feature Selector (MIFS) algorithms to select salient textural features that contain highly discriminatory information for multispectral imagery classification. The input candidate features are extracted from a SPOT High Resolution Visible(HRV) image using Wavelet Transform (WT) at levels (l = 1,2). The experimental results show that the selected textural features according to MIFS algorithms make the largest contribution to improve the classification accuracy than classical approaches such as Principal Components Analysis (PCA) and Linear Discriminant Analysis (LDA).

Keywords: Feature Selection, Texture, Mutual Information, Wavelet Transform, SVM classification, SPOT Imagery.

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Authors: Maatoug Hassine, Mourad Hrizi

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In this paper, we consider a geometric inverse source problem for the heat equation with Dirichlet and Neumann boundary data. We will reconstruct the exact form of the unknown source term from additional boundary conditions. Our motivation is to detect the location, the size and the shape of source support. We present a one-shot algorithm based on the Kohn-Vogelius formulation and the topological gradient method. The geometric inverse source problem is formulated as a topology optimization one. A topological sensitivity analysis is derived from a source function. Then, we present a non-iterative numerical method for the geometric reconstruction of the source term with unknown support using a level curve of the topological gradient. Finally, we give several examples to show the viability of our presented method.

Keywords: Geometric inverse source problem, heat equation, topological sensitivity, topological optimization, Kohn-Vogelius formulation.

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Authors: I. Fathollahi, J. Hesari, S. Azadmard, S. Oustan

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The relationships between Proteolysis and soluble calcium levels with hardness of cheese texture were investigated in Iranian UF white cheese during 90 d ripening. Cheeses were sampled in interior and exterior. Results showed that levels of proteolysis, soluble calcium and hardness of cheese texture changed significantly (p< 0.05) over ripening. Levels of proteolysis and hardness were significantly (p< 0.05) different in interior and exterior zones of cheeses. External zones of cheeses became softer and had higher levels of proteolysis compared to internal zones during ripening. The highest correlation coefficient (r2= 0.979; p<0.01) was observed between hardness and levels of pH 4.6-soluble nitrogen in exterior zones of cheese. These result showed that proteolysis can contribute to textural softening during ripening of Iranian UF white cheese.

Keywords: Calcium, Proteolysis, Softening, Ultrafiltration, White cheese.

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Authors: Rio G. L. D'Souza, K. Chandra Sekaran, A. Kandasamy

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The goal of Gene Expression Analysis is to understand the processes that underlie the regulatory networks and pathways controlling inter-cellular and intra-cellular activities. In recent times microarray datasets are extensively used for this purpose. The scope of such analysis has broadened in recent times towards reconstruction of gene networks and other holistic approaches of Systems Biology. Evolutionary methods are proving to be successful in such problems and a number of such methods have been proposed. However all these methods are based on processing of genotypic information. Towards this end, there is a need to develop evolutionary methods that address phenotypic interactions together with genotypic interactions. We present a novel evolutionary approach, called Phenomic algorithm, wherein the focus is on phenotypic interaction. We use the expression profiles of genes to model the interactions between them at the phenotypic level. We apply this algorithm to the yeast sporulation dataset and show that the algorithm can identify gene networks with relative ease.

Keywords: Evolutionary computing, gene expression analysis, gene networks, microarray data analysis, phenomic algorithms.

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Authors: Ahd Aljarf, Saad Amin

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Images are important source of information used as evidence during any investigation process. Their clarity and accuracy is essential and of the utmost importance for any investigation. Images are vulnerable to losing blocks and having noise added to them either after alteration or when the image was taken initially, therefore, having a high performance image processing system and it is implementation is very important in a forensic point of view. This paper focuses on improving the quality of the forensic images. For different reasons packets that store data can be affected, harmed or even lost because of noise. For example, sending the image through a wireless channel can cause loss of bits. These types of errors might give difficulties generally for the visual display quality of the forensic images. Two of the images problems: noise and losing blocks are covered. However, information which gets transmitted through any way of communication may suffer alteration from its original state or even lose important data due to the channel noise. Therefore, a developed system is introduced to improve the quality and clarity of the forensic images.

Keywords: Image Filtering, Image Reconstruction, Image Processing, Forensic Images.

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Authors: Wang Qiaowei, Gao Yujiang

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With the economic growth and rapid urbanization after the reform and openness, some of China's fast-growing cities have demolished former dwellings and built modern residential quarters. The blind, incomplete reference to western modern cities and the one-off construction lacking feedback mechanism have intensified such phenomenon, causing the citizen gradually expanded their living scale with the popularization of car traffic, and the peer-to-peer lifestyle gradually settled. The construction of large-scale commercial centers has caused obstacles to small business around the residential areas, leading to space for residents' interaction has been compressed. At the same time, the advocated Central Business District (CBD) model even leads to the unsatisfactory reconstruction of many historical blocks such as the Hangzhou Southern Song Dynasty Imperial Street. However, the popularity of historical spaces such as Wuzhen and Hongcun also indicates the collective memory and needs of the street space for Chinese residents. The evolution of Shanghai TianZiFang also proves the importance of the motivation of space participants in space construction in the context of the “top-down” construction model in China. In fact, there are frequent occurrences of “reconstruction”, which may redefine the space, in various residential areas. If these activities can be selectively controlled and encouraged, it will be beneficial to activate the public space as well as the residents’ intercourse, so that the traditional Chinese street space can be reconstructed in the context of modern cities.

Keywords: Rapid urbanization, traditional street space, space re-construction, bottom-up design.

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Authors: Vassilis S. Kodogiannis, John N. Lygouras

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In this research study, an intelligent detection system to support medical diagnosis and detection of abnormal lesions by processing endoscopic images is presented. The images used in this study have been obtained using the M2A Swallowable Imaging Capsule - a patented, video color-imaging disposable capsule. Schemes have been developed to extract texture features from the fuzzy texture spectra in the chromatic and achromatic domains for a selected region of interest from each color component histogram of endoscopic images. The implementation of an advanced fuzzy inference neural network which combines fuzzy systems and artificial neural networks and the concept of fusion of multiple classifiers dedicated to specific feature parameters have been also adopted in this paper. The achieved high detection accuracy of the proposed system has provided thus an indication that such intelligent schemes could be used as a supplementary diagnostic tool in endoscopy.

Keywords: Medical imaging, Computer aided diagnosis, Endoscopy, Neuro-fuzzy networks, Fuzzy integral.

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Authors: Marc C. Robini, Pierre-Jean Viverge, Yuemin Zhu, Jianhua Luo

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The standard approach to image reconstruction is to stabilize the problem by including an edge-preserving roughness penalty in addition to faithfulness to the data. However, this methodology produces noisy object boundaries and creates a staircase effect. The existing attempts to favor the formation of smooth contour lines take the edge field explicitly into account; they either are computationally expensive or produce disappointing results. In this paper, we propose to incorporate the smoothness of the edge field in an implicit way by means of an additional penalty term defined in the wavelet domain. We also derive an efficient half-quadratic algorithm to solve the resulting optimization problem, including the case when the data fidelity term is non-quadratic and the cost function is nonconvex. Numerical experiments show that our technique preserves edge sharpness while smoothing contour lines; it produces visually pleasing reconstructions which are quantitatively better than those obtained without wavelet-domain constraints.

Keywords:

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Authors: A. Ambia, T. Takemae, Y. Kosugi, M. Hongo

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Electric impedance imaging is a method of reconstructing spatial distribution of electrical conductivity inside a subject. In this paper, a new method of electrical impedance imaging using eddy current is proposed. The eddy current distribution in the body depends on the conductivity distribution and the magnetic field pattern. By changing the position of magnetic core, a set of voltage differences is measured with a pair of electrodes. This set of voltage differences is used in image reconstruction of conductivity distribution. The least square error minimization method is used as a reconstruction algorithm. The back projection algorithm is used to get two dimensional images. Based on this principle, a measurement system is developed and some model experiments were performed with a saline filled phantom. The shape of each model in the reconstructed image is similar to the corresponding model, respectively. From the results of these experiments, it is confirmed that the proposed method is applicable in the realization of electrical imaging.

Keywords: Back projection algorithm, electrical impedancetomography, eddy current, magnetic inductance tomography.

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Authors: Lu Yang, Meiyang Song, Xiang Yu, Wenhao Zhou, Chuntao Feng

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To address the problem that the FM continuous-wave (FMCW) radar extracts human vital sign signals which are susceptible to noise interference and low reconstruction accuracy, a detection scheme for the sign signals is proposed. Firstly, an improved complete ensemble empirical modal decomposition with adaptive noise (ICEEMDAN) algorithm is applied to decompose the radar-extracted thoracic signals to obtain several intrinsic modal functions (IMF) with different spatial scales, and then the IMF components are optimized by a backpropagation (BP) neural network improved by immune genetic algorithm (IGA). The simulation results show that this scheme can effectively separate the noise, accurately extract the respiratory and heartbeat signals and improve the reconstruction accuracy and signal to-noise ratio of the sign signals.

Keywords: Frequency modulated continuous wave radar, ICEEMDAN, BP Neural Network, vital signs signal.

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