2009MultiThresholdSegmentation

Abstract: Threshold selection is a critical step in computer vision. Immune systems, has inspired optimization algorithms known as Artificial Immune Optimization (AIO). AIO have been successfully applied to solve optimization problems. The Clonal Selection algorithm (CSA) is the most applied AIO method. It generates a response after an antigenic pattern is identified by an antibody. This works presents an image multi-threshold approach based on AIS optimization. The approach considers the segmentation task as an optimization process. The 1-D histogram of the image is approximated by adding several Gaussian functions whose parameters are calculated by the CSA. The mix of Gaussian functions approximates the histogram; each Gaussian function represents a pixel class (threshold point). The proposed approach is computationally efficient and does not require prior assumptions about the image. The algorithm demonstrated ability to perform automatic threshold selection.