Unsupervised color image segmentation using a dynamic color gradient thresholding algorithm
Guru Prashanth Balasubramanian, Eli S. Saber, Vladimir Mišić, Eric R. Peskin, Mark Q. Shaw · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2008
We propose a novel algorithm for unsupervised segmentation of color images. The proposed approach utilizes a dynamic color gradient thresholding scheme that guides the region growing process. Given a color image, a weighted vectorbased color gradient map is generated. Seeds are identified and a dynamic threshold is then used to perform reliable growing of regions on the weighted gradient map. Over-segmentation, if any, is addressed by a Similarity Measurebased region merging stage to produce the final segmented image. Comparative results demonstrate the effectiveness of this algorithm for color image segmentation.