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In this paper, a novel approach is proposed for shape classification based on the semi-supervised framework. For shape similarity-measuring problem, in order to avoid solving an NP problem produced by finding some affine transformation and to enhance its robustness for local changes of the shapes, we switch to compute an energy index defined by the degree of segmentation. The corresponding segmentation...
The accurate of printing plate dot size makes a significant impact on the reproduction of image gradient and color in the halftone image replication. Therefore, in order to eliminate the effect of noise, first of all we filter the acquisition of digital image, and then using threshold segmentation algorithm experiments on different dot image. In this paper two methods are proposed, and we named them...
In this paper, we present a new region based active contour algorithm for ultrasound image segmentation. An energy function based on a localized region-based active contour and shifted Rayleigh distribution is formulated. In our active contour framework, the target and background are represented as small local regions and the energy optimization is calculated at each point separately. The proposed...
In this paper, we study the problem of ultrasound image segmentation of kidney images. We propose a new region based active contour algorithm. The energy function of our algorithm is based on Chan-Vese energy function and the Bhattacharyya distance. In our framework, a curve is evolved to partition the image into two parts. Our algorithm minimizes the differences between each part and maximizes the...
High-speed defect detection method must be required for on-line inspection as well as accuracy based on vision technology. An appropriate real-time defect detection and location algorithm was investigated on surfaces of sequence circular objects in order to be used for on-line detection system. Firstly, difference image method and Otsu segmentation were employed in extracting defect regions. Secondly,...
Abnormal behavior detection refers to the problem of finding patterns in data that do not conform to expected behavior. Detection of abnormal behavior is an important area of research in computer vision and is also driven by a wide of application domains, such as smart video surveillance. In this paper, we present a novel based-energy approach for abnormal behavior detection. Use an adaptive optical...
The friction welding supersonic C scanned pictures will introduce the noise in process of gatherring and conversion, and the disturbance of the noise to the image effects image's quality, which brought the enormous difficulties for image characteristic information extraction and analysis. Therefore, this article will propose a denoising analysis method, which obtains the scanned picture to the experiment...
Subtle changes in brain tissue that reflect the pathological processes of disorders such as mild cognitive impairment (MCI) are much more difficult to observe on a patient's magnetic resonance imaging (MRI) scan than those obvious abnormalities such as large strokes or tumors. Thus, it is necessary to develop an automated computer-aided diagnosis (CAD) system which will be more efficient and accurate...
In this study, we present a systematic method for early detection of mild cognitive impairment (MCI) from magnetic resonance images (MRI) using image differences and clinical features. Early detection of MCI has pivotal importance to delay or prevent the onset of Alzheimer's disease (AD). Subjects were selected from the Open Access Series of Imaging Studies (OASIS)database and included 89 MCI subjects...
In the paper, an image mosaic algorithm based on SURF feature matching is proposed. The algorithm uses SURF operator which has strong robustness and superior performance to extract features instead of conventional SIFT operator. The extracted features are matched by a novel matching scheme - fast bidirectional matching. Then a RANSAC algorithm is applied to eliminate outliers and obtain the transformation...
In this paper, a novel multifocus image fusion method based on region selection is proposed. The basic idea is to select sharply focused regions from source images and to combine them together to reconstruct the resultant image. Region Acutance as a kind of superior sharpness criterion is introduced here for region segmentation. In view of the inevitably errors of selection, morphological operations...
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