Using Dynamic Programming for Solving Variational Problems in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast algorithm for active contours and curvature estimation
CVGIP: Image Understanding
SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
Interactive segmentation with Intelligent Scissors
Graphical Models and Image Processing
Introduction to Computer Graphics
Introduction to Computer Graphics
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In this paper, we propose a new image segmentation method based on the active contour. If we define a shape space as a set of all possible variations from the initial curve and we assume that the shape space is linear, it can be decomposed into the column space and the left null space of the shape matrix. In the proposed method, the shape space vector in the column space describes changes from the initial curve to the imaginary feature curve, and a dynamic graph search algorithm describes the detailed shape of the object in the left null space. Since we employ the shape matrix and the SUSAN operator to outline object boundaries, the proposed algorithm can ignore unwanted feature points generated by low-level image processing operations and is therefore applicable to images of the complex background. We can also compensate for limitations of the shape matrix with the dynamic graph search algorithm.