Active Contours with Prior Corner Detection
نویسندگان
چکیده
Deformable active contours are widely used in computer vision and image processing applications for image segmentation, especially in biomedical image analysis. The active contour or “snake” deforms towards a target object by controlling the internal, image and constraint forces. However, if the contour initialized with a lesser number of control points, there is a high probability of surpassing the sharp corners of the object during deformation of the contour. In this paper, a new technique is proposed to construct the initial contour by incorporating prior knowledge of significant corners of the object detected using the Harris operator. This new reconstructed contour begins to deform, by attracting the snake towards the targeted object, without missing the corners. Experimental results with several synthetic images show the ability of the new technique to deal with sharp corners with a high accuracy than traditional methods. Keywords—Active Contours, Image Segmentation, Harris Operator, Snakes
منابع مشابه
Active Contour Model for the Detection of Sharp Corners in Image Boundaries
Active contours are a form of curves that deform according to an energy minimizing function and are widely used in computer vision and image processing applications to extract features of interests from raw images acquired from an image capturing device. One of the major limitations in an active contour is its inability to converge accurately when the object of interest exhibits sharp corners. ...
متن کاملComparison of Discrete Curvature Estimators and Application to Corner Detection
Several curvature estimators along digital contours were proposed in recent works [1–3]. These estimators are adapted to non perfect digitization process and can process noisy contours. In this paper, we compare and analyse the performances of these estimators on several types of contours and we measure execution time on both perfect and noisy shapes. In a second part, we evaluate these estimat...
متن کاملAutomatic Graph Extraction from Color Images
An approach to symbolic contour extraction will be described that consists of three stages: enhancement, detection, and extraction of contours and corners. Contours and corners are enhanced by models of monkey cortical complex and endstopped cells. Detection of corners and local contour maxima is performed by selection of local maxima in both contour and corner enhanced images. These maxima for...
متن کاملContours Extraction Using Line Detection and Zernike Moment
Most of the contour detection methods suffers from some drawbacks such as noise, occlusion of objects, shifting, scaling and rotation of objects in image which they suppress the recognition accuracy. To solve the problem, this paper utilizes Zernike Moment (ZM) and Pseudo Zernike Moment (PZM) to extract object contour features in all situations such as rotation, scaling and shifting of object i...
متن کاملThe Role of Key-Points in Finding Contours
This paper describes a method for aggregating local edge evidences into coherent pieces of contour. An independent representation of corner and junction features provides suitable stop-conditions for the aggregation process and allows to divide contours into meaningful sub-strings, right from the beginning. The active role of corner and junction points makes the contours converge onto them and ...
متن کامل