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Face Recognition by Cognitive Discriminant Features | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 2، دوره 11، شماره 1، تیر 2020، صفحه 7-20 اصل مقاله (2.9 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2020.4205 | ||
| نویسندگان | ||
| Iman Firouzian* 1؛ Nematallah Firouzian2 | ||
| 1Faculty of Computer Engineering and IT, Shahrood University of Technology, Shahrood, Iran | ||
| 2Department of strategic management, Bank Melli Iran, Tehran, Iran | ||
| تاریخ دریافت: 13 مرداد 1398، تاریخ بازنگری: 16 آذر 1398، تاریخ پذیرش: 19 آذر 1398 | ||
| چکیده | ||
| Face recognition is still an active pattern analysis topic. Faces have already been treated as objects or textures, but human face recognition system takes a different approach in face recognition. People refer to faces by their most discriminant features. People usually describe faces in sentences like ``She's snub-nosed'' or ``he's got long nose'' or ``he's got round eyes'' and so like. These most discriminant features have been extracted by comparing a face with average face formed in one's mind. We have mathematically formulated the approach and placed importance upon the most discriminant features. We have explained feature processing and classification parts in details. We also explained the train and test phases of the proposed algorithm. We have compared the proposed classification part with 1-NN classifier to show the strength of the algorithm and reported the results. We have also compared the whole proposed algorithm with a well-known face recognition method, Eigenfaces and achieved promising results in different cases. | ||
| کلیدواژه‌ها | ||
| Face recognition؛ Most discriminant features؛ average face؛ Cognitive Pattern Recognition | ||
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آمار تعداد مشاهده مقاله: 16,124 تعداد دریافت فایل اصل مقاله: 1,902 |
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