Title :
Segmenting ripe tomato pictures based on the illumination irrelevant images
Author :
Xifeng Liang ; Zhengshuai Jiang
Author_Institution :
China Jiliang Univ., Hangzhou, China
Abstract :
In order to eliminate the impact of the illumination on the tomato image segmentation, the paper adopts a new method. The method is based on illumination irrelevant image, and uses minimum entropy criterion to calculate the illumination irrelevant angle of the given camera. We preprocess the colorful tomato image by the efficient median filter method, and obtain the illumination irrelevant image according to the formative principle of images. Then we segment the illumination irrelevant images using the improved Ostu segmentation method, and compare with the result of the segmentation images based on the chromatic aberration method. We also adopt the statistical threshold method in HIS color space to segment tomato images and study the influence of illumination. The experiment shows that the illumination irrelevant method can eliminate the influence of illumination effectively, and segments the objects accurately with the distinguished features.
Keywords :
aberrations; cameras; food products; image colour analysis; image segmentation; median filters; minimum entropy methods; statistical analysis; HIS color space; camera; chromatic aberration method; colorful tomato image preprocessing; illumination irrelevant angle calculation; illumination irrelevant image segmentation; improved Ostu segmentation method; median filter method; minimum entropy criterion; ripe tomato picture segmentation; statistical threshold method; tomato image segmentation; Entropy; Filtering algorithms; Histograms; Image color analysis; Image segmentation; Lighting; Object segmentation; Illumination irrelevant; Image segmentation; Median filter; Minimum entropy criterion; Tomato image;
Conference_Titel :
Natural Computation (ICNC), 2013 Ninth International Conference on
Conference_Location :
Shenyang
DOI :
10.1109/ICNC.2013.6818204