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This paper proposes a new method to detect objects in images. Boundaries contain shape of the objects. To detect objects in cluttered images, we use boundary fragments. Boundary fragments are obtained by our new training procedure. Poisson equation is used to divide edges and extract generic model of the object. Gaussian Mixture Model (GMM) is used to model shape of the object. This creates relation...
Lip segmentation is an essential step in audio-visual processing systems. In this paper, we incorporate the color and edge information in level set formulation, for extraction of lip contour. We build two initiative auxiliary images by mixing of different color spaces, to extract the landmark edges for upper and lower part of lip. The performance of this approach on VidTIMIT databases is tasted and...
Accurate pupil segmentation is the first and most important step for an iris recognition system. Current methods are based on fitting a model such as circle or ellipse to find and detect pupil, while these methods don't have sufficient accuracy and are sensitive to the specular spot reflection. In this paper, we utilize an optimized color mapping to increase the accuracy of pupil segmentation, regardless...
With a growing emphasis on human identification, iris recognition as a biometric identification has recently received increasing attention. The first step in iris recognition is segmentation. In this paper a new segmentation approach is offered which does not use any information of color or texture as the segmentation cues. Instead, we use random sample consensus method to fit an ellipse or a circle...
Silhouettes of an object provide rich information about its geometry. They can be effectively used for shape reconstruction under known object movement. In this paper we propose a robust method to estimate the object rigid motion information from space curves using double stereo rigs. For any sequence, some convinced space curves are extracted from edge contours in each stereo rig images. The curve...
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