Matlab / Projects / Project / Image processing


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Kodambakkam (Power House)

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Matlab / Projects / Project / Image processing

  1. 1. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 MATLAB 2011 1. Face Recognition by Information jointly contained in image Image Exploring space, scale and orientation domains can Processing Information Jointly provide rich important clues not seen in in Space, Scale and either individual of these domains. The Orientation position, spatial frequency and orientation selectivity properties are believed to have an important role in visual perception. This paper proposes a novel face representation and recognition approach by exploring information jointly in image space, scale and orientation domains. Specifically, the face image is first decomposed into different scale and orientation responses by convolving multiscale and multi-orientation Gabor filters. Second, local binary pattern analysis is used to describe the neighboring relationship not only in image space, but also in different scale and orientation responses. This way, information from different domains is explored to give a good face representation for recognition. Discriminant classification is then performed based upon weighted histogram intersection or conditional mutual information with linear discriminant analysis techniques. Extensive experimental results on FERET, AR, and FRGC ver 2.0 databases show the significant advantages of the proposed method over the existing ones. 2. Detection of We present methods for the detection of Image Architectural sites of architectural distortion in prior Processing Distortion in Prior mammograms of interval-cancer cases. We Mammograms hypothesize that screening mammograms obtained prior to the detection of cancer could contain subtle signs of early stages of breast cancer, in particular, architectural distortion. The methods are based upon Gabor filters, phase portrait analysis, a novel method for the analysis of the angular
  2. 2. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 spread of power, fractal analysis, Laws texture energy measures derived from geometrically transformed regions of interest (ROIs), and Haralicks texture features. With Gabor filters and phase portrait analysis, 4224 ROIs were automatically obtained from 106 prior mammograms of 56 interval-cancer cases, including 301 true-positive ROIs related to architectural distortion, and from 52 mammograms of 13 normal cases. For each ROI, the fractal dimension, the entropy of the angular spread of power, 10 Laws measures, and Haralicks 14 features were computed. The areas under the receiver operating characteristic curves obtained using the features selected by stepwise logistic regression and the leave-one-ROI- out method are 0.76 with the Bayesian classifier, 0.75 with Fisher linear discriminant analysis, and 0.78 with a single-layer feed-forward neural network. Free-response receiver operating characteristics indicated sensitivities of 0.80 and 0.90 at 5.8 and 8.1 false positives per image, respectively, with the Bayesian classifier and the leave-one-image-out method. 3. Enhanced With the widespread use of digital cameras, Image Assessment of the freehand wound imaging has become Processing Wound-Healing common practice in clinical settings. There Process by Accurate is however still a demand for a practical Multiview Tissue tool for accurate wound healing Classification assessment, combining dimensional measurements and tissue classification in a single user-friendly system. We achieved the first part of this objective by computing a 3-D model for wound measurements using uncalibrated vision techniques. We focus here on tissue classification from color and texture region descriptors
  3. 3. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 computed after unsupervised segmentation. Due to perspective distortions, uncontrolled lighting conditions and view points, wound assessments vary significantly between patient examinations. The main contribution of this paper is to overcome this drawback with a multiview strategy for tissue classification, relying on a 3-D model onto which tissue labels are mapped and classification results merged. The experimental classification tests demonstrate that enhanced repeatability and robustness are obtained and that metric assessment is achieved through real area and volume measurements and wound outline extraction. This innovative tool is intended for use not only in therapeutic follow-up in hospitals but also for telemedicine purposes and clinical research, where repeatability and accuracy of wound assessment are critical. 4. A New Supervised This paper presents a new supervised Image Method for Blood method for blood vessel detection in digital Processing Vessel retinal images. This method uses a neural Segmentation in network (NN) scheme for pixel Retinal Images by classification and computes a 7-D vector Using Gray-Level composed of gray-level and moment and Moment invariants-based features for pixel Invariants-Based representation. The method was evaluated Features on the publicly available DRIVE and STARE databases, widely used for this purpose, since they contain retinal images where the vascular structure has been precisely marked by experts. Method performance on both sets of test images is better than other existing solutions in literature. The method proves especially accurate for vessel detection in STARE images. Its application to this database (even when the NN was trained on the DRIVE database) outperforms all analyzed segmentation
  4. 4. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 approaches. Its effectiveness and robustness with different image conditions, together with its simplicity and fast implementation, make this blood vessel segmentation proposal suitable for retinal image computer analyses such as automated screening for early diabetic retinopathy detection. 5. Graph Run-Length The histopathological examination of tissue Image Matrices for specimens is essential for cancer diagnosis Processing Histopathological and grading. However, this examination is Image Segmentation subject to a considerable amount of observer variability as it mainly relies on visual interpretation of pathologists. To alleviate this problem, it is very important to develop computational quantitative tools, for which image segmentation constitutes the core step. In this paper, we introduce an effective and robust algorithm for the segmentation of histopathological tissue images. This algorithm incorporates the background knowledge of the tissue organization into segmentation. For this purpose, it quantifies spatial relations of cytological tissue components by constructing a graph and uses this graph to define new texture features for image segmentation. This new texture definition makes use of the idea of gray-level run- length matrices. However, it considers the runs of cytological components on a graph to form a matrix, instead of considering the runs of pixel intensities. Working with colon tissue images, our experiments demonstrate that the texture features extracted from “graph run-length matrices” lead to high segmentation accuracies, also providing a reasonable number of segmented regions. Compared with four other segmentation algorithms, the results show that the proposed algorithm is more
  5. 5. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 effective in histopathological image segmentation. 6. X-ray Categorization In this study we present an efficient image Image and Retrieval on the categorization and retrieval system applied Processing Organ and Pathology to medical image databases, in particular Level, Using Patch- large radiograph archives. The methodology Based Visual Words is based on local patch representation of the image content, using a “bag of visual words” approach. We explore the effects of various parameters on system performance, and show best results using dense sampling of simple features with spatial content, and a nonlinear kernel-based support vector machine (SVM) classifier. In a recent international competition the system was ranked first in discriminating orientation and body regions in X-ray images. In addition to organ-level discrimination, we show an application to pathology-level categorization of chest X-ray data, the most popular examination in radiology. The system discriminates between healthy and pathological cases, and is also shown to successfully identify specific pathologies in a set of chest radiographs taken from a routine hospital examination. This is a first step towards similarity-based categorization, which has a major clinical implications for computer-assisted diagnostics 7. Standard Deviation This letter proposes a new technique of Image for Obtaining the restoring images distorted by random- Processing Optimal Direction in valued impulse noise. The detection process the Removal of is based on finding the optimum direction, Impulse Noise by calculating the standard deviation in different directions in the filtering window. The tested pixel is deemed original if it is similar to the pixels in the optimum direction. Extensive simulations prove that the proposed technique has superior performance, when compared to other
  6. 6. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 existing methods, especially at high noise rates. 8. Removal of High A modified decision based unsymmetrical Image Density Salt and trimmed median filter algorithm for the Processing Pepper Noise restoration of gray scale, and color images Through Modified that are highly corrupted by salt and pepper Decision Based noise is proposed in this paper. The Unsymmetric proposed algorithm replaces the noisy pixel Trimmed Median by trimmed median value when other pixel Filter values, 0s and 255s are present in the selected window and when all the pixel values are 0s and 255s then the noise pixel is replaced by mean value of all the elements present in the selected window. This proposed algorithm shows better results than the Standard Median Filter (MF), Decision Based Algorithm (DBA), Modified Decision Based Algorithm (MDBA), and Progressive Switched Median Filter (PSMF). The proposed algorithm is tested against different grayscale and color images and it gives better Peak Signal-to- Noise Ratio (PSNR) and Image Enhancement Factor (IEF). 9. IMAGE Resolution In this correspondence, the authors propose Image Enhancement by an image resolution enhancement Processing Using Discrete and technique based on interpolation of the Stationary Wavelet high frequency subband images obtained by Decomposition discrete wavelet transform (DWT) and the input image. The edges are enhanced by introducing an intermediate stage by using stationary wavelet transform (SWT). DWT is applied in order to decompose an input image into different subbands. Then the high frequency subbands as well as the input image are interpolated. The estimated high frequency subbands are being modified by using high frequency subband obtained through SWT. Then all these subbands are combined to generate a new high resolution image by using inverse DWT
  7. 7. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 (IDWT). The quantitative and visual results are showing the superiority of the proposed technique over the conventional and state- of-art image resolution enhancement techniques. 10. Automatic Optic Disc Under the framework of computer-aided Image Detection From eye disease diagnosis, this paper presents Processing Retinal Images by a an automatic optic disc (OD) detection Line Operator technique. The proposed technique makes use of the unique circular brightness structure associated with the OD, i.e., the OD usually has a circular shape and is brighter than the surrounding pixels whose intensity becomes darker gradually with their distances from the OD center. A line operator is designed to capture such circular brightness structure, which evaluates the image brightness variation along multiple line segments of specific orientations that pass through each retinal image pixel. The orientation of the line segment with the minimum/maximum variation has specific pattern that can be used to locate the OD accurately. The proposed technique has been tested over four public datasets that include 130, 89, 40, and 81 images of healthy and pathological retinas, respectively. Experiments show that the designed line operator is tolerant to different types of retinal lesion and imaging artifacts, and an average OD detection accuracy of 97.4% is obtained. 11. Wavelet-Based In this letter, we propose an efficient one- Image Image Texture nearest-neighbor classifier of texture via Processing Classification Using the contrast of local energy histograms of Local Energy all the wavelet subbands between an input Histograms texture patch and each sample texture patch in a given training set. In particular, the contrast is realized with a discrepancy measure which is just a sum of
  8. 8. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 symmetrized Kullback-Leibler divergences between the input and sample local energy histograms on all the wavelet subbands. It is demonstrated by various experiments that our proposed method obtains a satisfactory texture classification accuracy in comparison with several current state-of- the-art texture classification approaches. 12. A Ringing-Artifact This paper proposes a new ringing-artifact Image Reduction Method reduction method for image resizing in a Processing for Block-DCT-Based block discrete cosine transform (DCT) Image Resizing domain. The proposed method reduces ringing artifacts without further blurring, whereas previous approaches must find a compromise between blurring and ringing artifacts. The proposed method consists of DCT-domain filtering and image-domain post-processing, which reduces ripples on smooth regions as well as overshoot near strong edges. By generating a mask map of the overshoot regions, we combine a ripple- reduced image and an overshoot-reduced image according to the mask map in the image domain to obtain a ringing-artifact reduced image. The experimental results show that the proposed method is computationally faster and produces visually finer images than previous ringing- artifact reduction approaches. 13. Automatic Exact Histogram equalization, which aims at Image Histogram information Processing Specification for maximization, is widely used in different Contrast ways to perform contrast Enhancement and enhancement in images. In this paper, an Visual System automatic exact Based Quantitative histogram specification technique is Evaluation proposed and used for global and local contrast enhancement of images. The desired histogram is obtained by first subjecting the image histogram to a modification
  9. 9. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 process and then by maximizing a measure that represents increase in information and decrease in ambiguity. A new method of measuring image contrast based upon local band-limited approach and center-surround retinal receptive field model is also devised in this paper. This method works at multiple scales (frequency bands) and combines the contrast measures obtained at different scales using -norm. In comparison to a few existing methods, the effectiveness of the proposed automatic exact histogram specification technique in enhancing contrasts of images is demonstrated through qualitative analysis and the proposed image contrast measure based quantitative analysis. 14. Fast Sparse Image Compressed sensing is a new paradigm for Image Reconstruction signal Processing Using recovery and sampling. It states that a Adaptive Nonlinear relatively small number Filtering of linear measurements of a sparse signal can contain most of its salient information and that the signal can be exactly reconstructed from these highly incomplete observations. The major challenge in practical applications of compressed sensing consists in providing efficient, stable and fast recovery algorithms which, in a few seconds, evaluate a good approximation of a compressible image from highly incomplete and noisy samples. In this paper, we propose to approach the compressed sensing image recovery
  10. 10. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 problem using adaptive nonlinear filtering strategies in an iterative framework, and we prove the convergence of the resulting two-steps iterative scheme. The results of several numerical experiments confirm that the corresponding algorithm possesses the required properties of efficiency, stability and low computational cost and that its performance is competitive with those of the state of the art algorithms. 15. Binary Tissue A pressure ulcer is a clinical pathology of Medical Classification on localized Imaging Wound Images With damage to the skin and underlying tissue Neural Networks caused by pressure, and Bayesian shear, or friction. Diagnosis, treatment, and Classifiers care of pressure ulcers are costly for health services. Accurate wound evaluation is a critical task for optimizing the efficacy of treatment and care. Clinicians usually evaluate each pressure ulcer by visual inspection of the damaged tissues, which is an imprecise manner of assessing the wound state. Current computer vision approaches do not offer a global solution to this particular problem. In this paper, a hybrid approach based on neural networks and Bayesian classifiers is used in the design of a computational system for automatic tissue identification in wound images. A mean shift procedure and a region-growing strategy are implemented for effective region segmentation. Color and texture features are extracted from these segmented regions. A
  11. 11. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 set of multilayer perceptrons is trained with inputs consisting of color and texture patterns, and outputs consisting of categorical tissue classes which are determined by clinical experts. This training procedure is driven by a -fold cross-validation method. Finally, a Bayesian committee machine is formed by training a Bayesian classifier to combine the classifications of the neural networks. Specific heuristics based on the wound topology are designed to significantly improve the results of the classification. We obtain high efficiency rates from a binary cascade approach for tissue identification. Results are compared with other similar machine-learning approaches, including multiclass Bayesian committee machine classifiers and support vector machines. The different techniques analyzed in this paper show high global classification accuracy rates. Our binary cascade approach gives high global performance rates (average sensitivity __ __, specificity __ __, and accuracy ____) and shows the highest average sensitivity score ( 86.3%) when detecting necrotic tissue in the wound 16. Removal of Artifacts We present a segmentation-based post- from JPEG processing method to remove compression Compressed artifacts from JPEG compressed Document document images. JPEG compressed images Images typically exhibit ringing and blocking artifacts, which can be objectionable to the viewer above certain
  12. 12. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 compression levels. The ringing is more dominant around textual regions while the blocking is more visible in natural images. Despite extensive research, reducing these artifacts in an effective manner still remains challenging. Document images are often segmented for various reasons. As a result, the segmentation information in many instances is available without requiring additional computation. We have developed a low computational cost method to reduce ringing and blocking artifacts for segmented document images. The method assumes the textual parts and pictorial regions in the document have been separated from each other by an automatic segmentation technique. It performs simple image processing techniques to clean out ringing and blocking artifacts from these regions. 17. A Low-Cost VLSI Image and video signals might be corrupted Implementation for by impulse Efficient noise in the process of signal acquisition Removal of Impulse and transmission. Noise In this paper, an efficient VLSI implementation for removing impulse noise is presented. Our extensive experimental results show that the proposed technique preserves the edge features and obtains excellent performances in terms of quantitative evaluation and visual quality. The design requires only low computational complexity and two line memory buffers. Its hardware cost is quite low. Compared with previous VLSI implementations, our design achieves better image quality with less hardware cost. Synthesis
  13. 13. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 results show that the proposed design yields a processing rate of about 167 M samples/second by using TSMC 0.18 m technology. 18. EVALUATION OF Microaneurysms (MAs) are the earliest sign RETINAL VESSEL of diabetic SEGMENTATION retinopathy and manifest as small reddish METHODS FOR spots on the retina. MICROANEURYSMS Generally, algorithm design for MAs DETECTION detection starts by separating the vascular system from the background for a posterior analysis of candidate MAs presence. Following this approach, this paper assesses three different methods for vessel segmentation and how they affect posterior MAs detection. The robustness in developing automatic screening systems for MAs detection is discussed and a methodology to detect candidate MAs in retinal images is introduced. The algorithm combines different vessel segmentation methods with region growing to evaluate which is the best to provide candidate MAs detection 19. Secret Protecting privacy for exchanging Signal Communication information Processing Using through the media has been a topic JPEG Double researched by many people. Compression Up to now, cryptography has always had its ultimate role in protecting the secrecy between the sender and the intended receiver. However, nowadays steganography techniques are used increasingly besides cryptography to add more protective layer to the hidden data. In this letter, we show
  14. 14. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 that the quality factor in a JPEG image can be an embedding space, and we discuss the ability of embedding a message to a JPEG image by managing JPEG quantization tables (QTs). In combination with some permutation algorithms, this scheme can be used as a tool for secret communication. The proposed method can achieve satisfactory decoded results with this straightforward JPEG double compression strategy. 20. Fast Vanishing Point Vision-based road detection in unstructured Image Detection in environments is a challenging problem as Processing Unstructured there are hardly any discernible and invariant features that can characterize the road or its boundaries in such environments. However, a salient and consistent feature of most roads or tracks regardless of type of the environments is that their edges, boundaries and even ruts and tire tracks left by previous vehicles on the path appear to converge into a single point known as the vanishing point. Hence, estimating this vanishing point plays a pivotal role in the determination of the direction of the road. In this paper, we propose a novel methodology based on image texture analysis for fast estimation of the vanishing point in challenging and unstructured roads. The key attributes of the methodology consist of Optimal Local Dominant Orientation Method (OLDOM) that uses joint activities of only four Gabor filters to precisely estimate the local dominant orientation at each pixel location in the image plane, weighting of each pixel based on its dominant orientation, and an adaptive distance based voting scheme for estimation of the vanishing point. A series
  15. 15. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 of quantitative and qualitative analyses are presented using natural data sets from the DARPA Grand Challenge projects to demonstrate the effectiveness and accuracy of the proposed methodology.