Title :
Fundus lesion identification based on the improved FCM and mathematical morphology
Author :
Hua, Li ; Zhang, Hui
Author_Institution :
Fac. of Comput. Eng., Huaiyin Inst. of Technol., Huaiyin, China
Abstract :
Fundus lesion identification is a worldwide problem. The traditional method has greater impact on human factors, subjective and cumbersome makes Fundus lesion identification Accuracy, objectivity and practicality not be guaranteed. To solve the above problem, an improved FCM algorithm for segmentation of Fundus lesion, the improved FCM algorithm clustering image segmentation Fundus lesion, and then remove the noise by mathematical morphology operations. Experimental results show that the algorithm can effectively identify the lesion in the Fundus image.
Keywords :
fuzzy set theory; human factors; image denoising; image segmentation; mathematical morphology; medical image processing; Fundus lesion identification; fuzzy c-means clustering algorithm; human factors; image segmentation; improved FCM algorithm; mathematical morphology operations; noise removal; Accuracy; Clustering algorithms; Image segmentation; Lesions; Noise; FCM; Fundus image; lesion identification; mathematical morphology;
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2012 IEEE 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2007-8
DOI :
10.1109/ICSESS.2012.6269420