Matlab image processing_2013_ieee

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MATLAB image processing ieee 2013 projects for Electronics Engineering

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Matlab image processing_2013_ieee

  1. 1. 1. Robust Face Recognition for Uncontrolled Pose and Illumination Changes Abstract — Face recognition has made significant advances in the last decade, but robust commercial applications are still lacking. Current authentication/identification applications are limited to controlled settings, e.g., limited pose and illumination changes, with the user usually aware of being screened and collaborating in the process. Among others, pose and illumination changes are limited. To address challenges from looser restrictions, this paper proposes a novel framework for real-world face recognition in uncontrolled settings named Face Analysis for Commercial Entities (FACE). Its robustness comes from normalization (“correction”) strategies to address pose and illumination variations. In addition, two separate image quality indices quantitatively assess pose and illumination changes for each biometric query, before submitting it to the classifier. Samples with poor quality are possibly discarded or undergo a manual classification or, when possible, trigger a new capture. After such filter, template similarity for matching purposes is measured using a localized version of the image correlation index. Finally, FACE adopts reliability indices, which estimate the “acceptability” of the final identification decision made by the classifier. 2. Reversible Watermarking Based on Invariant Image Classification and Dynamic Histogram Shifting Abstract — In this paper, we propose a new reversible watermarking scheme. One first contribution is a histogram shifting modulation which adaptively takes care of the local specificities of the image content. By applying it to the image prediction-errors and by considering their immediate neighborhood, the scheme we propose inserts data in textured areas where other methods fail to do so. Furthermore, our scheme makes use of a classification process for identifying parts of the image that can be watermarked with the most suited reversible IGSLABS Technologies Pvt Ltd, www.makefinalyearproject.com, Email: nandu@igslabs.com, Phone: 9590544567
  2. 2. modulation. This classification is based on a reference image derived from the image itself, a prediction of it, which has the property of being invariant to the watermark insertion. In that way, the watermark embedder and extractor remain synchronized for message extraction and image reconstruction. 3. Automatic Detection and Reconstruction of Building Radar Footprints From Single VHR SAR Images Abstract—The spaceborne synthetic aperture radar (SAR) systems CosmoSkyMed, TerraSAR-X, and TanDEM-X acquire imagery with very high spatial resolution (VHR), supporting various important application scenarios, such as damage assessment in urban areas after natural disasters. To ensure a reliable, consistent, and fast extraction of the information from the complex SAR scenes, automatic information extraction methods are essential. Focusing on the analysis of urban areas, which is of prime interest of VHR SAR, in this paper, we present a novel method for the automatic detection and 2-D reconstruction of building radar footprints from VHR SAR scenes. Unlike most of the literature methods, the proposed approach can be applied to single images. The method is based on the extraction of a set of low-level features from the images and on their composition to more structured primitives using a production system. Then, the concept of semantic meaning of the primitives is introduced and used for both the generation of building candidates and the radar footprint reconstruction. The semantic meaning represents the probability that a primitive belongs to a certain scattering class (e.g., double bounce, roof, facade) and has been defined in order to compensate for the lack of detectable features in single images. Indeed, it allows the selection of the most reliable primitives and footprint hypotheses on the basis of fuzzy membership grades. IGSLABS Technologies Pvt Ltd, www.makefinalyearproject.com, Email: nandu@igslabs.com, Phone: 9590544567
  3. 3. 4. Interactive Segmentation for Change Detection in Multispectral RemoteSensing Images Abstract—In this letter, we propose to solve the change detection (CD) problem in multitemporal remote-sensing images using interactive segmentation methods. The user needs to input markers related to change and no-change classes in the difference image. Then, the pixels under these markers are used by the support vector machine classifier to generate a spectral-change map. To enhance further the result, we include the spatial contextual information in the decision process using two different solutions based on Markov random field and level-set methods. 5. Estimating Information from Image Colors: An Application to Digital Cameras and Natural Scenes Abstract—The colors present in an image of a scene provide information about its constituent elements. But the amount of information depends on the imaging conditions and on how information is calculated. This work had two aims. The first was to derive explicitly estimators of the information available and the information retrieved from the color values at each point in images of a scene under different illuminations. 6. Airborne Vehicle Detection in Dense Urban Areas Using HoG Features Abstract—Vehicle detection has been an important research field for years as there are a lot of valuable applications, ranging from support of traffic planners to real-time traffic management. Especially detection of cars in dense urban areas is of interest due to the high traffic volume and the limited space. In city areas many car-like objects (e.g., dormers) appear which might lead to confusion. Additionally, the inaccuracy of road databases supporting the extraction process has to be handled in a proper way. This paper describes an IGSLABS Technologies Pvt Ltd, www.makefinalyearproject.com, Email: nandu@igslabs.com, Phone: 9590544567
  4. 4. integrated real-time processing chainwhich utilizes multiple occurrence of objects in images. 7. Histology Image Retrieval in Optimized Multifeature Spaces Abstract—Content-based histology image retrieval systems have shown great potential in supporting decision making in clinical activities, teaching, and biological research. In content-based image retrieval, feature combination plays a key role. It aims at enhancing the descriptive power of visual features corresponding to semantically meaningful queries. It is particularly valuable in histology image analysis where intelligent mechanisms are needed for interpreting varying tissue composition and architecture into histological concepts. This paper presents an approach to automatically combine heterogeneous visual features for histology image retrieval. The aim is to obtain the most representative fusion model for a particular keyword that is associated with multiple query images. The core of this approach is a multiobjective learning method, which aims to understand an optimal visual-semantic matching function by jointly considering the different preferences of the group of query images. The task is posed as an optimization problem, and a multiobjective optimization strategy is employed in order to handle potential contradictions in the query images associated with the same keyword. 8. Automatic License Plate Recognition (ALPR) Abstract—Automatic license plate recognition (ALPR) is the extraction of vehicle license plate information from an image or a sequence of images. The extracted information can be used with or without a database in many applications, such as electronic payment systems (toll payment, parking fee payment), and freeway and arterial monitoring systems for traffic surveillance. The ALPR uses either a color, black and white, or infrared camera to take images. The quality of the acquired images is a major factor in the success of IGSLABS Technologies Pvt Ltd, www.makefinalyearproject.com, Email: nandu@igslabs.com, Phone: 9590544567
  5. 5. the ALPR. ALPR as a reallife application has to quickly and successfully process license plates under different environmental conditions, such as indoors, outdoors, day or night time. It should also be generalized to process license plates from different nations, provinces, or states. These plates usually contain different colors, are written in different languages, and use different fonts; some plates may have a single color background and others have background images. The license plates can be partially occluded by dirt, lighting, and towing accessories on the car. 9. Context-Based Hierarchical Unequal Merging for SAR Image Segmentation Abstract—This paper presents an image segmentation method named Contextbased Hierarchical Unequal Merging for Synthetic aperture radar (SAR) Image Segmentation (CHUMSIS), which uses superpixels as the operation units instead of pixels. Based on the Gestalt laws, three rules that realize a new and natural way to manage different kinds of features extracted from SAR images are proposed to represent superpixel context. The rules are prior knowledge from cognitive science and serve as top-down constraints to globally guide the superpixel merging. The features, including brightness, texture, edges, and spatial information, locally describe the superpixels of SAR images and are bottom-up forces. While merging superpixels, a hierarchical unequalmerging algorithm is designed, which includes two stages: 1) coarse merging stage and 2) fine merging stage. The merging algorithm unequally allocates computation resources so as to spend less running time in the superpixels without ambiguity and more running time in the superpixels with ambiguity. IGSLABS Technologies Pvt Ltd, www.makefinalyearproject.com, Email: nandu@igslabs.com, Phone: 9590544567
  6. 6. 10. Context-Dependent Logo Matching and Recognition Abstract—We contribute, through this paper, to the design of a novel variational framework able to match and recognize multiple instances of multiple reference logos in image archives. Reference logos and test images are seen as constellations of local features (interest points, regions, etc.) and matched by minimizing an energy function mixing: 1) a fidelity term that measures the quality of feature matching, 2) a neighborhood criterion that captures feature co-occurrence/geometry, and 3) a regularization term that controls the smoothness of the matching solution. 11. Human Detection in Images via Piecewise Linear Support Vector Machines Abstract — Human detection in images is challenged by the view and posture variation problem. In this paper, we propose a piecewise linear support vector machine (PL-SVM) method to tackle this problem. The motivation is to exploit the piecewise discriminative function to construct a nonlinear classification boundary that can discriminate multiview and multiposture human bodies from the backgrounds in a high-dimensional feature space. A PL-SVM training is designed as an iterative procedure of feature space division and linear SVM training, aiming at the margin maximization of local linear SVMs. Each piecewise SVM model is responsible for a subspace, corresponding to a human cluster of a special view or posture. In the PL-SVM, a cascaded detector is proposed with block orientation features and a histogram of oriented gradient features. Extensive experiments show that compared with several recent SVM methods, our method reaches the state of the art in both detection accuracy and computational efficiency, and it performs best when dealing with low-resolution human regions in clutter backgrounds. IGSLABS Technologies Pvt Ltd, www.makefinalyearproject.com, Email: nandu@igslabs.com, Phone: 9590544567
  7. 7. 12. Learning-based, automatic 2D-to-3D image and video conversion Abstract — Despite a significant growth in the last few years, the availability of 3D content is still dwarfed by that of its 2D counterpart. In order to close this gap, many 2D-to-3D image and video conversion methods have been proposed. Methods involving human operators have been most successful but also timeconsuming and costly. Automatic methods, that typically make use of a deterministic 3D scene model, have not yet achieved the same level of quality for they rely on assumptions that are often violated in practice. In this paper, we propose a new class of method that are based on the radically different approach of learning the 2D-to-3D conversion from examples. We develop a method based on globally estimating the entire depth map of a query image directly from a repository of 3D images (image + depth pairs or stereopairs) using a nearest-neighbor regression type idea. We demonstrate both the efficacy and the computational efficiency of our methods on numerous 2D images and discuss their drawbacks and benefits. Although far from perfect, our results demonstrate that repositories of 3D content can be used for effective 2D-to-3D image conversion. An extension to video is immediate by enforcing temporal continuity of computed depth maps. 13. Automated Biometric Voice-Based Access Control in ATM Abstract — An automatic teller machine requires a user to pass an identity test before any transaction can be granted. The current method available for access control in ATM is based on smartcard. Efforts were made to conduct an interview with structured questions among the ATM users and the result proofed that a lot of problems was associated with ATM smartcard for access control. Among the problems are; it is very difficult to prevent another person from attaining and using a legitimate persons card, also conventional smartcard can be lost, duplicated, stolen or impersonated with accuracy. To address the IGSLABS Technologies Pvt Ltd, www.makefinalyearproject.com, Email: nandu@igslabs.com, Phone: 9590544567
  8. 8. problems, the paper proposed the use of biometric voice-based access control system in automatic teller machine. In the proposed system, access will be authorized simply by means of an enroll user speaking into a microphone attached to the automatic teller machine. There are 2 phases in implementation of the proposed system: first training phase, second testing or operational phase. 14. Steganography using Genetic Algorithm along with Visual Cryptography Abstract— Image steganography is an emerging field of research for secure data hiding and transmission over networks. The proposed system provides the best approach for Least Significant Bit (LSB) based steganography using Genetic Algorithm (GA) along with Visual Cryptography (VC). Original message is converted into cipher text by using secret key and then hidden into the LSB of original image. Genetic Algorithm and Visual Cryptography has been used for enhancing the security. Genetic Algorithm is used to modify the pixel location of stego image and the detection of this message is complex. Visual Cryptography is used to encrypt the visual information. It is achieved by breaking the image into two shares based on a threshold. The performance of the proposed system is experimented by performing steganalysis and conducting benchmarking test for analysing the parameters like Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The main aim of this paper is to design the enhanced secure algorithm which uses both steganography using Genetic Algorithm and Visual Cryptography to ensure improved security and reliability. 15. Human Skeleton Identification Methods to Reduce Uncomfortable IGSLABS Technologies Pvt Ltd, www.makefinalyearproject.com, Email: nandu@igslabs.com, Phone: 9590544567
  9. 9. Light from a Digital Projector Abstract-- When a speaker stands in front of a projector screen for a presentation, the eyes will be hurt by the direct light from the digital projector. This paper proposes a design to reduce the strong light by projecting a black round mask on the speaker's head. The black round mask is superimposed to the slide frame by the software of this design and the mask traces the speaker’s head. The Webcam captures the images from the speaker with the projector screen. The location of the speaker’s head is determined. This design efficiently continues to trace the head location. The computer uses this head location and superimposes a black round mask to reduce the uncomfortable feeling caused by the strong light of the projector. 16. IMAGE STITCHING WITH COMBINED MOMENT INVARIANTS AND SIFT FEATURES Abstract - Image stitching is used to combine multiple photographic images from camera network with overlapping field of view to produce panoramic view. With image stitching, the view is enlarged and the amount of information increases with the no. of images that are stitched. In the existing methods, the whole images from the adjacent views are considered thus leads to increase in both time and computational complexity. In this paper, an approach for image stitching using invariant moments combined with SIFT features is presented to reduce the time and computational complexity. It is observed that only a small portion of the adjacent view images are overlapped. Hence, the proposed method aims in detecting overlapping portion for extracting matching points. The overlapping regions are determined using gradient based dominant edge extraction and invariant moments. In the deduced region, the SIFT (Shift Invariant Feature Transform) features are extracted to determine the matching features. The registration is carried on with RANSAC (Random Sample IGSLABS Technologies Pvt Ltd, www.makefinalyearproject.com, Email: nandu@igslabs.com, Phone: 9590544567
  10. 10. Consensus) algorithm and final output mosaic is obtained by warping the images. The proposed approach results in reduced time and computational when compared to existing methods. 17. Vertical-Edge-Based Car-License-Plate Detection Method Abstract—This paper proposes a fast method for car-licenseplate detection (CLPD) and presents three main contributions. The first contribution is that we propose a fast vertical edge detection algorithm (VEDA) based on the contrast between the grayscale values, which enhances the speed of the CLPD method. After binarizing the input image using adaptive thresholding (AT), an unwanted-line elimination algorithm (ULEA) is proposed to enhance the image, and then, the VEDA is applied. The second contribution is that our proposed CLPD method processes very-low-resolution images taken by a web camera. After the vertical edges have been detected by the VEDA, the desired plate details based on color information are highlighted. Then, the candidate region based on statistical and logical operations will be extracted. Finally, an LP is detected. The third contribution is that we compare the VEDA to the Sobel operator in terms of accuracy, algorithm complexity, and processing time. IGSLABS Technologies Pvt Ltd, www.makefinalyearproject.com, Email: nandu@igslabs.com, Phone: 9590544567
  11. 11. Bio-Medical Based Image Processing 18. Lossless medical image compression by IWT Abstract - The proposed work is to compress the medical data without any loss(i.e. lossless). Medical information is either in multidimensional or multiresolution form, this creates enormous amount of data. Retrieval, Efficient storage, management and transmission of this voluminous data are highly complex. This technique combines integer transforms and JPEGLS Prediction to enhance the performance of lossless compression. 19. Analyzing Macular Edema In Diabetic Patients Abstract— Diabetic macular edema (DME) is an advanced symptom of diabetic retinopathy and can lead to irreversible vision loss. In this paper, a two-stage methodology for the detection and classification of DME severity from color fundus images is proposed. DME detection is carried out via a supervised learning approach using the normal fundus images. A feature extraction technique is introduced to capture the global characteristics of the fundus images and discriminate the normal from DME images. Disease severity is assessed using the neural networks. 20. Wavelet Based Image Fusion for Detection of Brain Tumor Abstract— Brain tumor, is one of the major causes for the increase in mortality among children and adults. Detecting the regions of brain is the major challenge in tumor detection. In the field of medical image processing, multi sensor images are widely being used as potential sources to detect brain tumor. In this paper, a wavelet based image fusion algorithm is applied on the Magnetic Resonance (MR) images and Computed Tomography (CT) images which are used as primary sources to extract the redundant and complementary information in order to enhance the tumor detection in the resultant fused IGSLABS Technologies Pvt Ltd, www.makefinalyearproject.com, Email: nandu@igslabs.com, Phone: 9590544567
  12. 12. image. The main features taken into account for detection of brain tumor are location of tumor and size of the tumor, which is further optimized through fusion of images using various wavelet transforms parameters. We discuss and enforce the principle of evaluating and comparing the performance of the algorithm applied to the images with respect to various wavelets type used for the wavelet analysis. The performance efficiency of the algorithm is evaluated on the basis of PSNR values. The obtained results are compared on the basis of PSNR with gradient vector field and big bang optimization. The algorithms are analyzed in terms of performance with respect to accuracy in estimation of tumor region and computational efficiency of the algorithms. Power Systems 21. Synchronous Detection and Digital control of Shunt Active Power Filter in Power Quality Improvement Abstract—Power Quality means to maintain purely sinusoidal current wave form in phase with a purely sinusoidal voltage wave form. Power quality improvement using traditional compensation methods include many disadvantages like electromagnetic interference, possible resonance, fixed compensation, bulkiness etc. So power system and power electronic engineers need to develop adjustable and dynamic solutions using custom power devices. These power conditioning equipments use static power electronic converters to improve the power quality of distribution system customers. The devices include Active Power Filter (APF), dynamic voltage restorer (DVR) and Unified Power Quality Conditioner (UPQC). APF is a compensator used to eliminate the disturbances in current. There are basically two types of APFs: the shunt type and the series type. This paper examines the control of Shunt Active IGSLABS Technologies Pvt Ltd, www.makefinalyearproject.com, Email: nandu@igslabs.com, Phone: 9590544567
  13. 13. Power Filter (SAPF) from two different aspects: Synchronous Detection Method (SDM) and digital control based on instantaneous power theory (p-q theory). Simulation results using MATLAB SIMULINK demonstrates the application of these methods to the control of APF. Moreover, this work shows that digital control provides better power quality improvement than SDM. IGSLABS Technologies Pvt Ltd, www.makefinalyearproject.com, Email: nandu@igslabs.com, Phone: 9590544567

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