Robust color segmentation algorithms in illumination variation conditions

<正>Changing illumination condition can change the result of image segmentation algorithm and reduce the intelligent recognition rate.A novel color image segmentation method robust to illumination variations is presented.The method is applied to the skin segmentation.Based on the hue preserving algorithm, the method reduces the dimensionality of the red-green-blue(RGB) space to one dimension,while keeping the hue of every pixel unchanging before and after space transformation.In the new color space,the skin color model is established using Gaussian model.Experimental results show that the method is robust to illumination variations,and has low computational complexity.     

An artificial immune approach for optical image based vision inspection

This paper presents a novel approach of visual inspection for texture surface defects. The approach uses artificial immune theory in learning the detection of texture defects. In this paper, texture defects are regards as non-self, and normal textures are regarded as self. Defect filters and segmentation thresholds used for defect detection are regarded as antibodies. The clonal selection algorithm stemmed from the natural immune system is employed to learn antibodies. Experimental results on textile image inspection are presented to illustrate the merit and feasibility of the proposed method.