Applying Intuitionistic Fuzzy Sets to Improve Fuzzy Content-based Image Retrieval Systems | ||
| Journal of AI and Data Mining | ||
| دوره 13، شماره 1، فروردین 2025، صفحه 63-73 اصل مقاله (1.78 M) | ||
| نوع مقاله: Original/Review Paper | ||
| شناسه دیجیتال (DOI): 10.22044/jadm.2025.14597.2568 | ||
| نویسندگان | ||
| Monireh Azimi Hemat1؛ Ezat Valipour* 2؛ Laya Ali Ahmadipoor1 | ||
| 1Department of Computer science, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran. | ||
| 2Department of Applied Mathematics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran. | ||
| چکیده | ||
| Visual features extracted from images in content-based image retrieval systems are inherently ambiguous. Consequently, applying fuzzy sets for image indexing in image retrieval systems has improved efficiency. In this article, the intuitionistic fuzzy sets are used to enhance the performance of the Fuzzy Content-Based Image Retrieval (F-CBIR) system. To this aim, an Intuitionistic Fuzzy Content-Based Image Retrieval (IF-CBIR) is proposed by applying intuitionistic fuzzy generators on fuzzy sets. Due to the diversity of the intuitionistic fuzzy distance measure, several are assessed in IF-CBIR; in these assessments, the measure with higher performance is identified. Finally, the proposed IF-CBIR and the existing crisp CBIR and F-CBIR simulate on Corel 5K and Corel 10K databases. The results show that our proposed method has higher (10-15%) precision compared to the mentioned methods. | ||
| کلیدواژهها | ||
| Image retrieval؛ Feature extraction؛ Fuzzy image retrieval؛ Intuitionistic fuzzy image retrieval؛ HSV color space | ||
| مراجع | ||
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