A novel approach for image segmentation

Image segmentation is the problem of finding the homogeneous regions (segments) in an image. Applications of image segmentation range from filtering of noisy images to problems of feature extraction and recognition. In this work we present a novel approach for image segmentation problems. The proposed technique is based on the idea of splitting the original image segmentation problem in two subproblems with lower computational complexity. First, a preliminary estimate of the segmented image gradient is found by solving a number of one-dimensional segmentation problems. In a second step, the results are merged together by enforcing that the obtained vector field is irrotational. At the cost of obtaining a "sub-optimal" solution, the computational advantage coming from the proposed decomposition can allow the implementation of sophisticated strategies that would be practically impossible to implement in a unique step. The results obtained on real and simulated image confirm the validity of the proposed approach.