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بکارگیری نُرم صفر هموار شده وزن‌دار در طبقه‌بندی نمایش تُنُک جهت شناسایی چهره | ||
| پدافند الکترونیکی و سایبری | ||
| مقاله 6، دوره 11، شماره 3 - شماره پیاپی 43، آبان 1402، صفحه 57-65 اصل مقاله (810.14 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| نویسندگان | ||
| محمّدسعید علمداری1؛ مسعود فاطمی* 2 | ||
| 1دانشجوی دکتری ،دانشگاه خواجه نصیر الدین طوسی، تهران، ایران | ||
| 2دانشیار،دانشگاه خواجه نصیر الدین طوسی، تهران، ایران | ||
| تاریخ دریافت: 24 فروردین 1402، تاریخ بازنگری: 23 خرداد 1402، تاریخ پذیرش: 14 مرداد 1402 | ||
| چکیده | ||
| طبقه‌بندی و شناسایی یکی از مهم‌ترین روش‌های استخراج اطلاعات از تصاویر می‌باشد که از میان آن‌ها، شناسایی تصاویر چهره به‌عنوان یکی از کارآمدترین ویژگی‌های بیومتریک در جهت شناسایی انسان‌ها همواره مورد توجه بوده است و درسالیان اخیر در این زمینه تحقیقات گسترده‌ای انجام شده است. تاکنون راهحلهای مختلفی برای شناسایی چهره از سوی محققان مطرح شده است ولی در میان آن‌ها استفاده از طبقه‌بندی نمایش تُنُک به‌عنوان راه‌حلی مؤثر و خاص مورد توجه قرار گرفته است. یکی از محاسن نمایش تُنُک، دریافت تصاویر ورودی بدون نیاز به استفاده از روش‌های استخراج ویژگی است، لذا در این مقاله روش پیشنهادی با بکارگیری نُرم صفر هموار شده وزن‌دار و بر اساس نمایش تُنُک جهت شناسایی چهره معرفی می‌شود. برای بررسی عملکرد روش پیشنهادی از دو پایگاه داده ORL و AR شامل تصاویر حالات مختلف چهره استفاده شده است که نتایج شبیه‌سازی شده نشان‌دهنده عملکرد بسیار مناسب روش نسبت به سایر روش‌های معروف در زمینه شناسایی چهره می‌باشد | ||
| کلیدواژه‌ها | ||
| شناسایی چهره؛ استخراج ویژگی؛ طبقه‌بندی نمایش تُنُک؛ نرم صفر هموار شده وزن‌دار | ||
| عنوان مقاله [English] | ||
| Applying weighted smoothed norm in sparse representation classification for face recognition | ||
| نویسندگان [English] | ||
| Mohammad Saeid Alamdari1؛ Masoud Fatemi2 | ||
| 1PhD student, Khwaja Nasiruddin Toosi University, Tehran, Iran | ||
| 2Associate Professor, Khwaja Nasiruddin Toosi University, Tehran, Iran | ||
| چکیده [English] | ||
| Classification and recognition is one of the most important methods of extracting information from images, and among them, facial image recognition as one of the most efficient biometric features for human identification has always been of interest, and extensive research has been conducted in this field in recent years. So far, various solutions for face recognition have been proposed by researchers, but among them, the use of Sparse representation classification has been considered as an effective and specific solution. One of the features of Sparse representation is to obtain features from input images without the need of feature extraction methods, therefore, in this article, the proposed method is aimed at applying weighted smoothed ℓ0 norm for face recognition using Sparse representation. To check the performance of the proposed method, ORL and AR databases including images of different facial expressions have been used, and the simulated results show that the method performs very well compared to other well-known methods in the field of face recognition. | ||
| کلیدواژه‌ها [English] | ||
| Face recongnition, Feature extraction, Sparse representation classification, Weighted smoothed l0 norm | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 303 تعداد دریافت فایل اصل مقاله: 364 |
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