Lettuce image target clustering segmentation based on MFICSC algorithm

Lettuce image target segmentation is the premise of the nondestructive detection of lettuce physiological information based on image processing. Because lettuce contains more water, the camera len is likely to occur reflex, leading to uneven gray distribution of lettuce leaf image. A modified image equalization algorithm is used to equalize the image gray. In this paper, the mixed fuzzy inter-cluster separation clustering(MFICSC) is applied in lettuce image target segmentation, which can make the distance between classes be maximum on the whole and can produce the fuzzy memberships and possibilities simultaneously. MFICSC can overcome the noise sensitivity and the coincident clusters problem. In the test, the MFICSC algorithm and Otsu algorithm were applied to lettuce image target segmentation respectively. The test results show that the MFICSC algorithm has better clustering accuracy, and its segmentation effect is superior to the one of traditional Otsu algorithm.