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Image can be parsed into two main categories of representation: structure shape and region texture. In this paper, the parallel multi-regions image restoration system is proposed in order to ensure the real-time application. This system is implemented on a dedicated cluster. With different number of regions, PMR system is executed on the same original image in order to obtain the best restoration...
A novel stereo matching algorithm using image segmentation is proposed in this paper. We investigate disparity distribution models (DDMs) on each segment for achieving very high quality results quickly without global optimization. A novel disparity plane fitting strategy based on the investigation is developed for accurately estimating disparity planes. We assign a frontal horizontal disparity plane...
In this paper, a novel algorithm for intensity inhomogeneous image segmentation is proposed. The presented method introduces a signed pressure force function using the local information of the image to be segmented. Thus, this model can work with heterogeneous images. In addition, by taking the advantages of Geodesic active contour (GAC) and Chan-Vese (C-V) model, the method could deal with objects...
Segmentation is an important step in medical image analysis. This process is crucial but challenging due to inhomogeneneity in intensity of images. In addition, the images are often corrupted by noise and with contrast edges. There are some approaches aiming to cope with this kind of images such as: region growing, region competition, watershed segmentation, global thresholding, and active contour...
In this paper, a novel model for intensity inhomogeneous image segmentation is proposed. The proposed model uses the local information of the image to be segmented; concurrently, it incorporates the geodesic active contour (GAC) model into Chan-Vese (C-V) model in energy function. Thus, the proposed model is effective when dealing with intensity inhomogeneous images. Practical experiments prove that...
In this paper, a novel algorithm for image segmentation is proposed. The presented method embeds the Geodesic Active Contour (GAC) model into the region based method. The proposed model adds a term that relates the region information of image to be segmented to the energy function of Geodesic Active Contour model. As a result, a new energy function is established. This method therefore includes both...
This paper introduces a DSP optimization model based on data structure transformation and memory schedule for real-time image process. This model implements 4 critical methods: image block, image dimension reduction, DMA transfer and ping-pong cache, which makes use of DSP hardware feature and optimizes the data schedule among the external and internal memory and CPU, while processing 2D digital signal...
Great challenges are faced in the offline recognition of cursive Arabic handwriting. This paper presents a segmentation-free system based on Hidden Markov Model (HMM) to handle this problem, where character segmentation stage is avoided prior to recognition. The system first extracts a set of robust features on binary handwritten images by sliding windows. Then the proposed system builds character...
Recognition of degraded characters is a challenging problem in the field of document image analysis. Two main reasons for degradation of characters are due to noise scanning and intrinsic degradation caused by font variations. The degradation of characters is mostly in the form of characters being broken at several places which hinders their recognition of OCR systems. Many OCRs have been designed...
Object or region based image processing can be performed more efficiently with information pertaining locations that are visually salient to human perception with the aid of a saliency map. The saliency map is a master topological map having the possible locations of objects or regions which a human perceived as important/salient. In this paper, a method to compute the saliency map in the wavelet...
K-Means algorithm is an unsupervised clustering algorithm that classifies the input data points into multiple classes based on their inherent distance from each other. Success of k-means color image segmentation depends on parameter k. If numbers of clusters are estimated correctly, k-means image segmentation can provide good results. This paper proposes a novel method based on edge detection to estimate...
A method aimed at minimizing image noise while optimizing contrast of image subtle features based on nonsubsampled contourlet transform is presented in this paper. Nonsubsampled contourlet transform, which is a shift-invariant version of the contourlet transform, has better performance in representing image edges than separable wavelet for its anisotropy, directionality and shift-invariance, and is...
The rubber seals material is not rigid, and easy deformed. To realize rubber seals size measurement automatically, computer vision technology based on non-contact measurement is employed, invariant as standard of size measurement is studied. The full and smooth contour is segmented using de-noised with average template and gray thresh with iterative method, and chain code description is modified according...
Mammography is the most effective method for the early diagnosis and treatment of breast Cancer diseases. However, data sets collected by image sensors are generally contaminated by noise. This ensures the need for image enhancement to aid interpretation. This paper introduces an efficient enhancement algorithm of digital mammograms based on wavelet analysis and modified mathematical morphology. In...
The watershed algorithm is the method of choice for image segmentation in the field of mathematical morphology, which is run simple, good performance and can better extract the contour of moving object. This paper used the watershed algorithm definition by immersion, and modify it, achieved good results after apply to core particles image segmentation. Experiments show that the method of watershed...
Image segmentation is a relevant research area in Computer Vision, and several methods of segmentation have been proposed in the last 40 years. This paper presents the implementation using the GUI feature of the MATLAB and one best result can be selected for any algorithm using the subjective evaluation. This process can help to find out the best suitable value of parameters for the segmentation of...
Recent research has been devoted to detecting people in images and videos. In this paper, a human detection method based on Histogram of Oriented Gradients (HoG) features and human body ratio estimation is presented. We utilized the discriminative power of HoG features for human detection, and implemented motion detection and local regions sliding window classifier, to obtain a rich descriptor set...
Pedestrian detection is one of the most popular research areas in video processing and it is vital for video surveillance systems. In this paper, we present a real-time pedestrian detection system based on Dalal and Triggs's human detection framework with the use of image segmentation and virtual mask. Image segmentation enables the system to focus only on the region of interest whereas the virtual...
We present a novel approach for generating stylized artistic rendering of caricatures from a given face image, with the ability to map any one of the main six expressions and control the degree of its expressiveness on the generated caricature. Our method achieves this by manipulating the facial appearance and expressivity of the caricature, using quadratic deformation model representations of facial...
In the paper a novel improved genetic algorithm is proposed based on the maximum entropy for thresholding image segmentation. First of all, the encoded mode is made and the maximum entropy function is selected as the key adaptation genetic algorithm, and then the initial group is generated by roulette selection algorithm to the next generation for the best individual, which can improve the global...
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