Search results for: Human facial image

Authors: Veni.S , K.A.Narayanankutty

Abstract:

For about two decades scientists have been developing techniques for enhancing the quality of medical images using Fourier transform, DWT (Discrete wavelet transform),PDE model etc., Gabor wavelet on hexagonal sampled grid of the images is proposed in this work. This method has optimal approximation theoretic performances, for a good quality image. The computational cost is considerably low when compared to similar processing in the rectangular domain. As X-ray images contain light scattered pixels, instead of unique sigma, the parameter sigma of 0.5 to 3 is found to satisfy most of the image interpolation requirements in terms of high Peak Signal-to-Noise Ratio (PSNR) , lower Mean Squared Error (MSE) and better image quality by adopting windowing technique.

Keywords: Hexagonal lattices, Gabor filter, Interpolation, imageprocessing.

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Authors: Asmatullah Chaudhry, Anwar M. Mirza

Abstract:

We present a general comparison of punctual kriging based image restoration for different neighbourhood sizes. The formulation of the technique under consideration is based on punctual kriging and fuzzy concepts for image restoration in spatial domain. Three different neighbourhood windows are considered to estimate the semivariance at different lags for studying its effect in reduction of negative weights resulted in punctual kriging, consequently restoration of degraded images. Our results show that effect of neighbourhood size higher than 5x5 on reduction in negative weights is insignificant. In addition, image quality measures, such as structure similarity indices, peak signal to noise ratios and the new variogram based quality measures; show that 3x3 window size gives better performance as compared with larger window sizes.

Keywords: Image restoration, punctual kriging, semi-variance, structure similarity index, negative weights in punctual kriging.

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Authors: Zacharenia I. Garofalaki, John T. Amorginos, John N. Ellinas

Abstract:

This paper presents the development of a robot car that can track the motion of an object by detecting its color through an Android device. The employed computer vision algorithm uses the OpenCV library, which is embedded into an Android application of a smartphone, for manipulating the captured image of the object. The captured image of the object is subjected to color conversion and is transformed to a binary image for further processing after color filtering. The desired object is clearly determined after removing pixel noise by applying image morphology operations and contour definition. Finally, the area and the center of the object are determined so that object’s motion to be tracked. The smartphone application has been placed on a robot car and transmits by Bluetooth to an Arduino assembly the motion directives so that to follow objects of a specified color. The experimental evaluation of the proposed algorithm shows reliable color detection and smooth tracking characteristics.

Keywords: Android, Arduino Uno, Image processing, Object motion detection, OpenCV library.

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Authors: D. R. Awang Rambli, S. Sulaiman, M.Y. Nayan, A.R. Asoruddin

Abstract:

Existing image-based virtual reality applications allow users to view image-based 3D virtual environment in a more interactive manner. User could “walkthrough"; looks left, right, up and down and even zoom into objects in these virtual worlds of images. However what the user sees during a “zoom in" is just a close-up view of the same image which was taken from a distant. Thus, this does not give the user an accurate view of the object from the actual distance. In this paper, a simple technique for zooming in an object in a virtual scene is presented. The technique is based on the 'hotspot' concept in existing application. Instead of navigation between two different locations, the hotspots are used to focus into an object in the scene. For each object, several hotspots are created. A different picture is taken for each hotspot. Each consecutive hotspot created will take the user closer to the object. This will provide the user with a correct of view of the object based on his proximity to the object. Implementation issues and the relevance of this technique in potential application areas are highlighted.

Keywords: Hotspots, image-based VR, camera zooms, virtualreality.

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Authors: D.Gnanadurai, V.Sadasivam

Abstract:

This frame work describes a computationally more efficient and adaptive threshold estimation method for image denoising in the wavelet domain based on Generalized Gaussian Distribution (GGD) modeling of subband coefficients. In this proposed method, the choice of the threshold estimation is carried out by analysing the statistical parameters of the wavelet subband coefficients like standard deviation, arithmetic mean and geometrical mean. The noisy image is first decomposed into many levels to obtain different frequency bands. Then soft thresholding method is used to remove the noisy coefficients, by fixing the optimum thresholding value by the proposed method. Experimental results on several test images by using this method show that this method yields significantly superior image quality and better Peak Signal to Noise Ratio (PSNR). Here, to prove the efficiency of this method in image denoising, we have compared this with various denoising methods like wiener filter, Average filter, VisuShrink and BayesShrink.

Keywords: Wavelet Transform, Gaussian Noise, ImageDenoising, Filter Banks and Thresholding.

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Authors: Saudagar Abdul Khader Jilani, Syed Abdul Sattar

Abstract:

Image compression plays a vital role in today-s communication. The limitation in allocated bandwidth leads to slower communication. To exchange the rate of transmission in the limited bandwidth the Image data must be compressed before transmission. Basically there are two types of compressions, 1) LOSSY compression and 2) LOSSLESS compression. Lossy compression though gives more compression compared to lossless compression; the accuracy in retrievation is less in case of lossy compression as compared to lossless compression. JPEG, JPEG2000 image compression system follows huffman coding for image compression. JPEG 2000 coding system use wavelet transform, which decompose the image into different levels, where the coefficient in each sub band are uncorrelated from coefficient of other sub bands. Embedded Zero tree wavelet (EZW) coding exploits the multi-resolution properties of the wavelet transform to give a computationally simple algorithm with better performance compared to existing wavelet transforms. For further improvement of compression applications other coding methods were recently been suggested. An ANN base approach is one such method. Artificial Neural Network has been applied to many problems in image processing and has demonstrated their superiority over classical methods when dealing with noisy or incomplete data for image compression applications. The performance analysis of different images is proposed with an analysis of EZW coding system with Error Backpropagation algorithm. The implementation and analysis shows approximately 30% more accuracy in retrieved image compare to the existing EZW coding system.

Keywords: Accuracy, Compression, EZW, JPEG2000, Performance.

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Authors: Swetha Kurup, Sridhar G., Sridhar V.

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In this paper we present a novel technique for data hiding in binary document images. We use the concept of entropy in order to identify document specific least distortive areas throughout the binary document image. The document image is treated as any other image and the proposed method utilizes the standard document characteristics for the embedding process. Proposed method minimizes perceptual distortion due to embedding and allows watermark extraction without the requirement of any side information at the decoder end.

Keywords: Entropy, Steganography, Watermarking.

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Authors: A. Mitra, Y. V. Subba Rao, S. R. M. Prasanna

Abstract:

This paper proposes a new approach for image encryption using a combination of different permutation techniques. The main idea behind the present work is that an image can be viewed as an arrangement of bits, pixels and blocks. The intelligible information present in an image is due to the correlations among the bits, pixels and blocks in a given arrangement. This perceivable information can be reduced by decreasing the correlation among the bits, pixels and blocks using certain permutation techniques. This paper presents an approach for a random combination of the aforementioned permutations for image encryption. From the results, it is observed that the permutation of bits is effective in significantly reducing the correlation thereby decreasing the perceptual information, whereas the permutation of pixels and blocks are good at producing higher level security compared to bit permutation. A random combination method employing all the three techniques thus is observed to be useful for tactical security applications, where protection is needed only against a casual observer.

Keywords: Encryption, Permutation, Good key, Combinationalpermutation, Pseudo random index generator.

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Authors: Susmitha Vekkot, Pancham Shukla

Abstract:

In this paper, we focus on the fusion of images from different sources using multiresolution wavelet transforms. Based on reviews of popular image fusion techniques used in data analysis, different pixel and energy based methods are experimented. A novel architecture with a hybrid algorithm is proposed which applies pixel based maximum selection rule to low frequency approximations and filter mask based fusion to high frequency details of wavelet decomposition. The key feature of hybrid architecture is the combination of advantages of pixel and region based fusion in a single image which can help the development of sophisticated algorithms enhancing the edges and structural details. A Graphical User Interface is developed for image fusion to make the research outcomes available to the end user. To utilize GUI capabilities for medical, industrial and commercial activities without MATLAB installation, a standalone executable application is also developed using Matlab Compiler Runtime.

Keywords: Filter mask, GUI, hybrid architecture, image fusion, Matlab Compiler Runtime, wavelet transform.

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Authors: Shang-Lin Hsieh, Lung-Yao Hsu, I-Ju Tsai

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This paper proposes a copyright protection scheme for color images using secret sharing and wavelet transform. The scheme contains two phases: the share image generation phase and the watermark retrieval phase. In the generation phase, the proposed scheme first converts the image into the YCbCr color space and creates a special sampling plane from the color space. Next, the scheme extracts the features from the sampling plane using the discrete wavelet transform. Then, the scheme employs the features and the watermark to generate a principal share image. In the retrieval phase, an expanded watermark is first reconstructed using the features of the suspect image and the principal share image. Next, the scheme reduces the additional noise to obtain the recovered watermark, which is then verified against the original watermark to examine the copyright. The experimental results show that the proposed scheme can resist several attacks such as JPEG compression, blurring, sharpening, noise addition, and cropping. The accuracy rates are all higher than 97%.

Keywords: Color image, copyright protection, discrete wavelet transform, secret sharing, watermarking.

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Authors: S. Sowmyayani, P. Arockia Jansi Rani

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Fall detection is one of the challenging problems in elderly care system. The objective of this paper is to identify falls in elderly care system. In this paper, an efficient fall detection method is proposed to identify falls using correlation factor and Motion History Image (MHI). The proposed method is tested on URF (University of Rzeszow Fall detection) dataset and evaluated with some efficient measures like sensitivity, specificity, precision and classification accuracy. It is compared with other recent methods. The experimental results substantially proved that the proposed method achieves 1.5% higher sensitivity when compared to other methods.

Keywords: Pearson correlation coefficient, motion history image, human shape identification.

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Authors: Ching-Sheng Hsu, Young-Chang Hou

Abstract:

In this paper, a novel copyright protection scheme for digital images based on Visual Cryptography and Statistics is proposed. In our scheme, the theories and properties of sampling distribution of means and visual cryptography are employed to achieve the requirements of robustness and security. Our method does not need to alter the original image and can identify the ownership without resorting to the original image. Besides, our method allows multiple watermarks to be registered for a single host image without causing any damage to other hidden watermarks. Moreover, it is also possible for our scheme to cast a larger watermark into a smaller host image. Finally, experimental results will show the robustness of our scheme against several common attacks.

Keywords: Copyright protection, digital watermarking, samplingdistribution, visual cryptography.

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Authors: Huafeng Wang, Yunhong Wang, Yuan Cao

Abstract:

During the past several years, face recognition in video has received significant attention. Not only the wide range of commercial and law enforcement applications, but also the availability of feasible technologies after several decades of research contributes to the trend. Although current face recognition systems have reached a certain level of maturity, their development is still limited by the conditions brought about by many real applications. For example, recognition images of video sequence acquired in an open environment with changes in illumination and/or pose and/or facial occlusion and/or low resolution of acquired image remains a largely unsolved problem. In other words, current algorithms are yet to be developed. This paper provides an up-to-date survey of video-based face recognition research. To present a comprehensive survey, we categorize existing video based recognition approaches and present detailed descriptions of representative methods within each category. In addition, relevant topics such as real time detection, real time tracking for video, issues such as illumination, pose, 3D and low resolution are covered.

Keywords: Face recognition, video-based, survey

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Authors: F. F. Howard, C. B. Boye, I. Yakubu, J. S. Y. Kuma

Abstract:

One of the ways that could be used for the production of land use and land cover maps by a procedure known as image classification is the use of the remote sensing technique. Numerous elements ought to be taken into consideration, including the availability of highly satisfactory Landsat imagery, secondary data and a precise classification process. The goal of this study was to classify and map the land use and land cover of the study area using remote sensing and Geospatial Information System (GIS) analysis. The classification was done using Landsat 8 satellite images acquired in December 2020 covering the study area. The Landsat image was downloaded from the USGS. The Landsat image with 30 m resolution was geo-referenced to the WGS_84 datum and Universal Transverse Mercator (UTM) Zone 30N coordinate projection system. A radiometric correction was applied to the image to reduce the noise in the image. This study consists of two sections: the Land Use/Land Cover (LULC) and Accuracy Assessments using the confusion and contingency matrix and the Kappa coefficient. The LULC classifications were vegetation (agriculture) (67.87%), water bodies (0.01%), mining areas (5.24%), forest (26.02%), and settlement (0.88%). The overall accuracy of 97.87% and the kappa coefficient (K) of 97.3% were obtained for the confusion matrix. While an overall accuracy of 95.7% and a Kappa coefficient of 0.947 were obtained for the contingency matrix, the kappa coefficients were rated as substantial; hence, the classified image is fit for further research.

Keywords: Confusion Matrix, contingency matrix, kappa coefficient, land used/ land cover, accuracy assessment.

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Authors: Mario Mastriani

Abstract:

This paper describes a novel projection algorithm, the Projection Onto Span Algorithm (POSA) for wavelet-based superresolution and removing speckle (in wavelet domain) of unknown variance from Synthetic Aperture Radar (SAR) images. Although the POSA is good as a new superresolution algorithm for image enhancement, image metrology and biometric identification, here one will use it like a tool of despeckling, being the first time that an algorithm of super-resolution is used for despeckling of SAR images. Specifically, the speckled SAR image is decomposed into wavelet subbands; POSA is applied to the high subbands, and reconstruct a SAR image from the modified detail coefficients. Experimental results demonstrate that the new method compares favorably to several other despeckling methods on test SAR images.

Keywords: Projection, speckle, superresolution, synthetic aperture radar, thresholding, wavelets.

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Authors: M. Almas Anjum, M. Younus Javed, A. Basit

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In this paper a new approach to face recognition is presented that achieves double dimension reduction, making the system computationally efficient with better recognition results and out perform common DCT technique of face recognition. In pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results change with change in face image resolution and provide optimal results when arriving at a certain resolution level. In the proposed model of face recognition, initially image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Due to increased computational speed and feature extraction potential of Discrete Cosine Transform (DCT), it is applied on face image. A subset of coefficients of DCT from low to mid frequencies that represent the face adequately and provides best recognition results is retained. A tradeoff between decimation factor, number of DCT coefficients retained and recognition rate with minimum computation is obtained. Preprocessing of the image is carried out to increase its robustness against variations in poses and illumination level. This new model has been tested on different databases which include ORL , Yale and EME color database.

Keywords: Biometrics, DCT, Face Recognition, Illumination, Computation, Feature extraction.

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Authors: Arslan Qamar Malik, Jehanzeb Ahmad

Abstract:

The paper presents a novel idea to control computer mouse cursor movement with human eyes. In this paper, a working of the product has been described as to how it helps the special people share their knowledge with the world. Number of traditional techniques such as Head and Eye Movement Tracking Systems etc. exist for cursor control by making use of image processing in which light is the primary source. Electro-oculography (EOG) is a new technology to sense eye signals with which the mouse cursor can be controlled. The signals captured using sensors, are first amplified, then noise is removed and then digitized, before being transferred to PC for software interfacing.

Keywords: Human Computer Interaction, Real-Time System, Electro-oculography, Signal Processing.

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Authors: Jayadevan R., Jayant V. Kulkarni, Suresh N. Mali, Hemant K. Abhyankar

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An important step in studying the statistics of fingerprint minutia features is to reliably extract minutia features from the fingerprint images. A new reliable method of computation for minutiae feature extraction from fingerprint images is presented. A fingerprint image is treated as a textured image. An orientation flow field of the ridges is computed for the fingerprint image. To accurately locate ridges, a new ridge orientation based computation method is proposed. After ridge segmentation a new method of computation is proposed for smoothing the ridges. The ridge skeleton image is obtained and then smoothed using morphological operators to detect the features. A post processing stage eliminates a large number of false features from the detected set of minutiae features. The detected features are observed to be reliable and accurate.

Keywords: Minutia, orientation field, ridge segmentation, textured image.

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Authors: Yasuyuki Takahashi, Hayato Ishimura, Masao Miyagawa, Teruhito Mochizuki

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Quantitative measurement of myocardium perfusion is possible with single photon emission computed tomography (SPECT) using a semiconductor detector. However, accumulation of ^99mTc-tetrofosmin in the liver may make it difficult to assess that accurately in the inferior myocardium. Our idea is to reduce the high accumulation in the liver by using dynamic SPECT imaging and a technique called time subtraction. We evaluated the performance of a new SPECT system with a cadmium-zinc-telluride solid-state semi- conductor detector (Discovery NM 530c; GE Healthcare). Our system acquired list-mode raw data over 10 minutes for a typical patient. From the data, ten SPECT images were reconstructed, one for every minute of acquired data. Reconstruction with the semiconductor detector was based on an implementation of a 3-D iterative Bayesian reconstruction algorithm. We studied 20 patients with coronary artery disease (mean age 75.4 ± 12.1 years; range 42-86; 16 males and 4 females). In each subject, 259 MBq of ^99mTc-tetrofosmin was injected intravenously. We performed both a phantom and a clinical study using dynamic SPECT. An approximation to a liver-only image is obtained by reconstructing an image from the early projections during which time the liver accumulation dominates (0.5~2.5 minutes SPECT image-5~10 minutes SPECT image). The extracted liver-only image is then subtracted from a later SPECT image that shows both the liver and the myocardial uptake (5~10 minutes SPECT image-liver-only image). The time subtraction of liver was possible in both a phantom and the clinical study. The visualization of the inferior myocardium was improved. In past reports, higher accumulation in the myocardium due to the overlap of the liver is un-diagnosable. Using our time subtraction method, the image quality of the ^99mTc-tetorofosmin myocardial SPECT image is considerably improved.

Keywords: 99mTc-tetrofosmin, dynamic SPECT, time subtraction, semiconductor detector.

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Authors: Yee Yee Htun, Dr. Khaing Khaing Aye

Abstract:

Morphological operators transform the original image into another image through the interaction with the other image of certain shape and size which is known as the structure element. Mathematical morphology provides a systematic approach to analyze the geometric characteristics of signals or images, and has been applied widely too many applications such as edge detection, objection segmentation, noise suppression and so on. Fuzzy Mathematical Morphology aims to extend the binary morphological operators to grey-level images. In order to define the basic morphological operations such as fuzzy erosion, dilation, opening and closing, a general method based upon fuzzy implication and inclusion grade operators is introduced. The fuzzy morphological operations extend the ordinary morphological operations by using fuzzy sets where for fuzzy sets, the union operation is replaced by a maximum operation, and the intersection operation is replaced by a minimum operation. In this work, it consists of two articles. In the first one, fuzzy set theory, fuzzy Mathematical morphology which is based on fuzzy logic and fuzzy set theory; fuzzy Mathematical operations and their properties will be studied in details. As a second part, the application of fuzziness in Mathematical morphology in practical work such as image processing will be discussed with the illustration problems.

Keywords: Binary Morphological, Fuzzy sets, Grayscalemorphology, Image processing, Mathematical morphology.

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Authors: A. Seddiki, M. Djebbouri, D. Guerchi

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Medical imaging produces human body pictures in digital form. Since these imaging techniques produce prohibitive amounts of data, compression is necessary for storage and communication purposes. Many current compression schemes provide a very high compression rate but with considerable loss of quality. On the other hand, in some areas in medicine, it may be sufficient to maintain high image quality only in region of interest (ROI). This paper discusses a contribution to the lossless compression in the region of interest of Scintigraphic images based on SPIHT algorithm and global transform thresholding using Huffman coding.

Keywords: Global Thresholding Transform, Huffman Coding, Region of Interest, SPIHT Coding, Scintigraphic images.

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Authors: Ayman A. Aly, Abdallah A. Alshnnaway

Abstract:

The general idea behind the filter is to average a pixel using other pixel values from its neighborhood, but simultaneously to take care of important image structures such as edges. The main concern of the proposed filter is to distinguish between any variations of the captured digital image due to noise and due to image structure. The edges give the image the appearance depth and sharpness. A loss of edges makes the image appear blurred or unfocused. However, noise smoothing and edge enhancement are traditionally conflicting tasks. Since most noise filtering behaves like a low pass filter, the blurring of edges and loss of detail seems a natural consequence. Techniques to remedy this inherent conflict often encompass generation of new noise due to enhancement. In this work a new fuzzy filter is presented for the noise reduction of images corrupted with additive noise. The filter consists of three stages. (1) Define fuzzy sets in the input space to computes a fuzzy derivative for eight different directions (2) construct a set of IFTHEN rules by to perform fuzzy smoothing according to contributions of neighboring pixel values and (3) define fuzzy sets in the output space to get the filtered and edged image. Experimental results are obtained to show the feasibility of the proposed approach with two dimensional objects.

Keywords: Additive noise, edge preserving filtering, fuzzy image filtering, noise reduction, two dimensional mechanical images.

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Authors: M.Sujaritha, S. Annadurai

Abstract:

An adaptive spatial Gaussian mixture model is proposed for clustering based color image segmentation. A new clustering objective function which incorporates the spatial information is introduced in the Bayesian framework. The weighting parameter for controlling the importance of spatial information is made adaptive to the image content to augment the smoothness towards piecewisehomogeneous region and diminish the edge-blurring effect and hence the name adaptive spatial finite mixture model. The proposed approach is compared with the spatially variant finite mixture model for pixel labeling. The experimental results with synthetic and Berkeley dataset demonstrate that the proposed method is effective in improving the segmentation and it can be employed in different practical image content understanding applications.

Keywords: Adaptive; Spatial, Mixture model, Segmentation, Color.

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Authors: Changhyuk Jang, Keechul Jung

Abstract:

Human pose estimation can be executed using Active Shape Models. The existing techniques for applying to human-body research using Active Shape Models, such as human detection, primarily take the form of silhouette of human body. This technique is not able to estimate accurately for human pose to concern two arms and legs, as the silhouette of human body represents the shape as out of round. To solve this problem, we applied the human body model as stick-figure, “skeleton". The skeleton model of human body can give consideration to various shapes of human pose. To obtain effective estimation result, we applied background subtraction and deformed matching algorithm of primary Active Shape Models in the fitting process. The images which were used to make the model were 600 human bodies, and the model has 17 landmark points which indicate body junction and key features of human pose. The maximum iteration for the fitting process was 30 times and the execution time was less than .03 sec.

Keywords: Active shape models, skeleton, pose estimation.

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Authors: Williams S. Ebhota, Ckikaodili Virginia Ugwu

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Human ability is a major source of constraint to manufacturing industries in Nigeria. This paper therefore, discusses the importance of human influences on manufacturing and consequently to industrialization and National development. In this paper, the development of manufacturing was anchored on two main factors; Infrastructural Capacity Development (ICD) and Human Capacity Development (HCD). However, a wider view was given to the HCD and the various contemporary human capacity issues militating against manufacturing in Nigeria. It went further to discuss various ways of acquiring and upgrading workers’ skills and finally, suggestions were made on how to tackle the onerous human capacity issues in manufacturing.

Keywords: Manufacturing, Human, Capacity, Development, Innovation.

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Authors: Lewis E. Hibell, Honghai Liu, David J. Brown

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This paper presents the use of a newly created network structure known as a Self-Delaying Dynamic Network (SDN) to create a high resolution image from a set of time stepped input frames. These SDNs are non-recurrent temporal neural networks which can process time sampled data. SDNs can store input data for a lifecycle and feature dynamic logic based connections between layers. Several low resolution images and one high resolution image of a scene were presented to the SDN during training by a Genetic Algorithm. The SDN was trained to process the input frames in order to recreate the high resolution image. The trained SDN was then used to enhance a number of unseen noisy image sets. The quality of high resolution images produced by the SDN is compared to that of high resolution images generated using Bi-Cubic interpolation. The SDN produced images are superior in several ways to the images produced using Bi-Cubic interpolation.

Keywords: Image Enhancement, Neural Networks, Multi-Frame.

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Authors: F. C. Calnegru

Abstract:

This article presents a computationally tractable probabilistic model for the relation between the complex wavelet coefficients of two images of the same scene. The two images are acquisitioned at distinct moments of times, or from distinct viewpoints, or by distinct sensors. By means of the introduced probabilistic model, we argue that the similarity between the two images is controlled not by the values of the wavelet coefficients, which can be altered by many factors, but by the nature of the wavelet coefficients, that we model with the help of hidden state variables. We integrate this probabilistic framework in the construction of a new image registration algorithm. This algorithm has sub-pixel accuracy and is robust to noise and to other variations like local illumination changes. We present the performance of our algorithm on various image types.

Keywords: Complex wavelet transform, image registration, modeling using hidden state variables, probabilistic similaritymeasure.

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Authors: J. Umamaheswari, G. Radhamani

Abstract:

This paper describes about the process of recognition and classification of brain images such as normal and abnormal based on PSO-SVM. Image Classification is becoming more important for medical diagnosis process. In medical area especially for diagnosis the abnormality of the patient is classified, which plays a great role for the doctors to diagnosis the patient according to the severeness of the diseases. In case of DICOM images it is very tough for optimal recognition and early detection of diseases. Our work focuses on recognition and classification of DICOM image based on collective approach of digital image processing. For optimal recognition and classification Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Support Vector Machine (SVM) are used. The collective approach by using PSO-SVM gives high approximation capability and much faster convergence.

Keywords: Recognition, classification, Relaxed Median Filter, Adaptive thresholding, clustering and Neural Networks

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Authors: V. B. Bastos, M. P. Lima, P. R. G. Kurka

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This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.

Keywords: Simulation, visual navigation, mobile robot, data visualization.

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Authors: Dibyendu Ghoshal, Pinaki Pratim Acharjya

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Image segmentation process based on mathematical morphology has been studied in the paper. It has been established from the first principles of the morphological process, the entire segmentation is although a nonlinear signal processing task, the constituent wise, the intermediate steps are linear, bilinear and conformal transformation and they give rise to a non linear affect in a cumulative manner.

Keywords: Image segmentation, linear transform, bilinear transform, conformal transform, mathematical morphology.

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