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Digital image processing is shifting the information analysis paradigms in a variety of systems whereas that it is becoming highly viable. Medicine has made the most of image processing by enhancing decision-making through computer-aided diagnosis (CAD) systems. CAD image models support medical inferences by extracting key visual features and classifying regions of interest. Linear parametric system...
One of the major research areas attracting much interest is face recognition. This is due to the growing need of detection and recognition in the modern days' industrial applications. However, this need is conditioned with the high performance standards that these applications require in terms of speed and accuracy. In this work we present a comparison between two main techniques of face recognition...
Cinnamon cultivation is the main income source of a set of areas in Sri Lanka. Peeling cinnamon is a complex task of the cinnamon harvesting process after identifying the matured cinnamon trees. Expertise knowledge is essential to identify matured trees using the traditional method. Otherwise, it may cause the wastage of cinnamon, by cutting immature cinnamon trees. This research addresses the automated...
Dermatological diseases are the most prevalent diseases worldwide. Despite being common, its diagnosis is extremely difficult and requires extensive experience in the domain. In this research paper, we provide an approach to detect various kinds of these diseases. We use a dual stage approach which effectively combines Computer Vision and Machine Learning on clinically evaluated histopathological...
Computational visual atention models aims to emulate the Human Visual System performance in selecting relevant features for efficient visual scene processing. As a result, visual saliency maps highlights relevant visual patterns in an image, possibly associated with objects or specific concepts. In the analysis of medical images, this allows the radiologist or clinical expert to focus the attention...
The region of interests (ROI) detection plays an important role in the remote sensing data processing and analysis. In this paper, a new region of interest detection method based on salient feature clustering for remote sensing images is proposed. Four steps are included in the proposed method. First, the information salient feature maps are constructed by computing the spectrum information and histograms...
This paper proposes a novel model, called Similarity Based on Visual Attention Features (SimVisual), to enhance the similarity analysis between images by considering features extracted from salient regions mapped by visual attention models. Visual attention models have demonstrated to be very useful for encoding perceptual semantic information of the image content. Thus, aggregating saliency features...
3D Model Reconstruction is of the most important part in the field of Reverse Engineering. It has now become feasible to use this method to create a 3D model of existing product, component for CAD/CAM applications. Various phases of reverse engineering and 3D reconstruction are reviewed in details along the methodology involved within these stages. Data acquisition is the most crucial stage of 3d...
Strokes of Chinese characters are extracted from a picture of calligraphy work by image processing methods. By analyzing the stroke's centerline location, width, constriction velocity and curvature, a feature matrix is constructed. By editing the feature matrix, we synthesize images of Chinese calligraphy in new styles.
The classification of stored grain pests based on the computer vision technology is studied in this paper. Combining with compressed sensing sparse representation theory, a novel stored grain pests classification model which meets the RIP condition is proposed. First, the grain pests based on sparse representation classification model is built, and then a condition which satisfied the RIP pest classification...
The perception-based approach of feature extraction methods for CBIR has been summarized. It has proposed an experimental analysis of mathematical modeling of textural contents for images, having a perceptual meaning and application such as coarseness, directionality, contrast, and busyness. An objective is to find an effective method to estimate perceptual features. So a cumulative use of computational...
Content Based Image Retrieval is very hottest research area in computer vision and image processing. To perceive arbitrary natural scene from complex environment is a challenging issue in visual imaging and processing research area. Neural Network is a grid of “neuron like” nodes, in this paper we follow towards Neural Network (NN), is committed to contributing a new technical concept for the scene...
On the basis of image processing, the Chinese character recognition model of non specific people is researched based on hidden Markov model (HMM), and an improved isolated Chinese character recognition model is proposed based on HMM and scale invariant feature transform (SIFT) algorithm. The SIFT algorithm is used to extract the feature points of Chinese character, the SIFT feature point extraction...
A large number of filters has been proposed to compute local gradients in grayscale images, usually having as goal the adequate characterization of edges. A significant portion of such filters are antisymmetric with respect to the origin. In this work we propose to generalize those filters by incorporating an explicit evaluation of the tonal difference. More specifically, we propose to apply restricted...
To achieve enhanced image recognition, it is necessary to accurately extract the contour of the recognition target from the input image in a preprocessing step. Contour extraction methods based on the active contour model(Snakes) require the operator to specify the parameter values that best catch the shape of the target. However, it is difficult to guess the parameter values since the relationship...
In this paper, we present and discuss high performance implementation of a wide class of image processing applications on a low-power massively parallel SIMD architecture, the ClearSpeed CSX700. We present parallel implementation results for four classes of image processing applications: feature detection (Harris Corner Detector), stereo vision (a class of SSD like algorithms), model estimation (RANSAC),...
The prompt search and rescue of lifesaving target is very important in the case that a marine casualty occurs. To detect the small target in the wide views over the sea, we have proposed a machine vision system to aid search and rescue on the sea, which combines remote sensing, radar, infrared with visual light technology. One of the detection methods in this system, which is based on visual attention...
There is an increased interest in developing an automatic facial expression analysis to recognize and model real human faces. In this paper, a local model-based approach for extraction of facial feature points from 2D still images and feature points tracking in image sequences are presented. It presents an algorithm that extracts the local oriented edges of intransient facial features (eyebrows, eyes,...
This paper presents a novel approach to locate corresponding regions between two views in urban environments despite the presence of repetitive structures and widely separated views. First we extract hypotheses of building facades, each defined by a rectangular region. The inputs from each pair of regions in two images derive a projective transformation model. Extracted lines and points are used to...
Humans are adept at identifying informative regions in individual images, but it is a slow and often tedious task to identify the salient parts of every image in a large corpus. A machine, on the other hand, can sift through a large amount of data quickly, but machine methods for identifying salient regions are unreliable. In this paper, we develop a new method for identifying salient regions in images...
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