Image Retrieval based on Multi-features using Fuzzy Set

  • سال انتشار: 1401
  • محل انتشار: مجله هوش مصنوعی و داده کاوی، دوره: 10، شماره: 4
  • کد COI اختصاصی: JR_JADM-10-4_011
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 166
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نویسندگان

M. Azimi hemat

Department of Computer Engineering and Information Technology, Payame Noor University, Iran.

F. Shamsezat Ezat

Department of Computer Science, Faculty of Mathematics and Computer, Fasa University, Fasa, Iran.

M. Kuchaki Rafsanjani

Department of Computer Science, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran .

چکیده

In content-based image retrieval (CBIR), the visual features of the database images are extracted, and the visual features database is assessed to find the images closest to the query image. Increasing the efficiency and decreasing both the time and storage space of indexed images is the priority in developing image retrieval systems. In this research, an efficient system is proposed for image retrieval by applying fuzzy techniques, which are advantageous in increasing the efficiency and decreasing the length of the feature vector and storage space. The effect of increasing the considered content features' count is assessed to enhance image retrieval efficiency. The fuzzy features consist of color, statistical information related to the spatial dependency of the pixels on each other, and the position of image edges. These features are indexed in fuzzy vector format ۱۶, ۳, and ۱۶ lengths. The extracted vectors are compared through the fuzzy similarity measures, where the most similar images are retrieved. To evaluate the proposed systems' performance, this system and three other non-fuzzy systems where fewer features are of concern were implemented. These four systems are tested on a database containing ۱۰۰۰ images, and the results indicate improvement in the retrieval precision and storage space.

کلیدواژه ها

Image Retrieval, Feature extraction, fuzzy color histogram,, image edges, spatial dependency of pixels

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