نوع مقاله : مقاله پژوهشی
نویسندگان
1 واحد تهران جنوب - دانشگاه آزاد اسلامی
2 South Tehran Branch - Islamic Azad University
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Recently, image segmentation based on graph cut methods has shown remarkable performance on a set of image data. Although the kernel graph cut method provides good performance, its performance is highly dependent on the mapping of data to the transform space and image features. Entropy-based kernel graph cut method is suitable for segmentation of textured images. However, the quality of its segmentation is affected by the extracting kernel centers quality. This article examines the segmentation of textural images using the proposed weighted entropy and VGG16-based kernel graph cut method. Using the advantages of kernel space, the objective function consists of two data components to transfer the data standard deviation of each area in the segmented image and the adjustment component. The proposed method, while taking advantage of the appropriate computational load of graph-based methods, will be a suitable alternative for textural image segmentation. Experimental results have been taken on a set of well-known datasets that include textural shapes in order to evaluate the effectiveness of the algorithm in compared to state-of-the-art methods in the field of kernel graph cut.
کلیدواژهها [English]
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