Pomegranate MR image analysis using fuzzy clustering algorithms

摘要: In this paper, the process of pomegranate magnetic resonance (MR) images was studied . Its internal structure is composed tissue and seeds , which indicate dependency between maturity quality. The latter properties are important in pomegranate’s sorting cannot be measured manually. an automatic algorithm propose d to segment s Since intensities calyx stem MR image closely related that soft tissue, their corresponding pixels therefore labeled same class tissues. order solve problem, exact shape first extracted from background using active contour models (ACMs). Then, removed morphological filters. We have also proposed improved version fuzzy c-means (FCM), spatial FCM (SFCM), for segmentation pomegranate. SFCM realized by incorporating neighborhood information into standard modifying membership weighting each cluster. employs adjacent leading improvement results. It thus outperforms other techniques like FCM, even presence Gaussian, salt pepper speckle noises. Keywords: MRI, pomegranate, segmentation, c-means, filter