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Journal of Artificial Intelligence and Data Mining، جلد ۷، شماره ۴، صفحات ۵۰۷-۵۱۹
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عنوان انگلیسی Image Segmentation using Improved Imperialist Competitive Algorithm and a Simple Post-processing
چکیده انگلیسی مقاله Image segmentation is a fundamental step in many of image processing applications. In most cases the image's pixels are clustered only based on the pixels' intensity or color information and neither spatial nor neighborhood information of pixels is used in the clustering process. Considering the importance of including spatial information of pixels which improves the quality of image segmentation, and using the information of the neighboring pixels, causes enhancing of the accuracy of segmentation. In this paper the idea of combining the K-means algorithm and the Improved Imperialist Competitive algorithm is proposed. Also before applying the hybrid algorithm, a new image is created and then the hybrid algorithm is employed. Finally, a simple post-processing is applied on the clustered image. Comparing the results of the proposed method on different images, with other methods, shows that in most cases, the accuracy of the NLICA algorithm is better than the other methods.
کلیدواژه‌های انگلیسی مقاله
نویسندگان مقاله V. Naghashi |
Computer Engineering, University College of Nabi Akram, Rahahan, Tabriz, Iran.

Sh. Lotfi |
Computer Science, University of Tabriz, Tabriz, Iran.

نشانی اینترنتی http://jad.shahroodut.ac.ir/article_1465_2ad4291fcc7695bdd431b925bdb3290a.pdf
فایل مقاله اشکال در دسترسی به فایل - ./files/site1/rds_journals/480/article-480-2063333.pdf
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زبان مقاله منتشر شده en
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