Title :
A New Image Segmentation Algorithm Based on Fuzzy Logical
Author_Institution :
Coll. of Inf. Sci. & Eng., Shenyang Ligong Univ., Shenyang, China
Abstract :
In order to determine the optimal thresholds in image segmentation, an effective image threshold segmentation method is presented that base on Fuzzy logic. A new fuzzy entropy is defined, that is not only related to the membership (fuzzy domain) but also related to the probability distribution (space domain), it can respond to the variety of image input information. In addition, by introducing a novel particle swarm optimization (PSO) algorithm, the optimal threshold can be gotten to find the optimization parameters of the membership, so that one image can be segmented by using the threshold. Using our novel algorithm to segment images, we can get a better result than that of most threshold segmentation algorithm.
Keywords :
entropy; fuzzy logic; fuzzy set theory; image segmentation; particle swarm optimisation; probability; threshold logic; fuzzy entropy; fuzzy logical; image segmentation algorithm; image threshold segmentation method; membership function; optimal thresholds determination; particle swarm optimization algorithm; probability distribution; Educational institutions; Entropy; Fuzzy logic; Fuzzy set theory; Fuzzy sets; Image processing; Image segmentation; Information science; Particle swarm optimization; Probability distribution;
Conference_Titel :
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4994-1
DOI :
10.1109/ICIECS.2009.5362908
