بررسی روش های تشخیص چهره مبتنی بر الگوریتم های یادگیری عمیق
محورهای موضوعی : نوآوري و خلاقيت
پژمان غلام نژاد
1
,
احسان شریفی
2
1 - دانشگاه علوم و فنون هوایی شهید ستاری
2 - دانشگاه هوایی شهید ستاری
کلید واژه: تشخیص چهره عمیق, الگوریتمِ HMAX, الگوریتمِ B-HMAX, روش های تشخیصِ چهره, فناوریِ تشخیصِ چهره مبتنی بر بیومتریک.,
چکیده مقاله :
امروزه با رشد فناوری اطلاعات، تشخیص چهره یک مساله چالش برانگیز در زمینه تجزیه و تحلیل تصویر و بینایی رایانه است و به همین دلیل در چند سال گذشته به خاطر کاربردهای فراوان در حوزه های مختلف مورد توجه بسیاری قرار گرفته است. روش های زیادی برای پیاده سازی این فناوری مورد استفاده قرار می گیرد، اما روش کلی بر مبنای مقایسه مشخصه های خاصی از چهره افراد با یک پایگاه داده یا مجموعه اطلاعاتی از پیش ذخیره شده ( که می تواند حاصل نمونه گیری از چهره افراد باشد) است. فناوری های مبتنی بر بیومتریک در سال‌های اخیر به عنوان امیدوارکننده ترین گزینه برای تشخیص هویت افراد، شناخته شده اند. به منظور پیاده-سازی تشخیص چهره از روش های متفاوتی استفاده می شود. در این مقاله، مروری بر برخی از روش های شناخته شده پردازش تصویر انجام می شود و مزایا و معایب طرح های ذکر شده در آن بررسی شده است. همچنین فناوری های پیاده سازی سیستم های تشخیص چهره معرفی می گردد. سپس الگوریتم های تشخیص چهره بر اساس مشخصه های بیومتریک دسته بندی و معرفی می شوند. علاوه بر این، ضمن معرفی الگوریتم های مدل سلسله مراتبی و ایکس، مدل سلسله مراتبی باینری و ایکس، به بیانِ مفهوم ساختار تشخیصِ چهره ی عمیق، پرداخته شده است و برخی از جدیدترین الگوریتم های تولید شده برای این منظور ذکر شده است. در پایان، برخی از مهم ترین موارد کاربرد سیستم های تشخیص چهره مورد بررسی قرار گرفته است. هدف از این مقاله، معرفی و بیان الگوریتم های یادگیری عمیق در تشخیص چهره و بیان چالش های موجود می باشد.
Today, with the growth of information technology, face recognition is a challenging issue in the image and vision analysis of computers, and for this reason, in many years, many attention has been considered for many applications in different domains. There are many methods for implementing this technology, but the general method based on the comparison of certain characteristics of the faces of individuals with a database or pre-stored information set (which can be sampled from the sampling Be the faces of people). Biometric-based technologies have been recognized in recent years as the most promising option for identifying individuals. Different methods are used in order to implement facial diagnosis. In this paper, a review of some of the well-known image processing methods is performed and the advantages and disadvantages of the designs listed in it have been investigated. Also, the implementation of facial diagnostic systems is introduced. Then, face diagnostic algorithms are categorized and introduced based on biometric characteristics. In addition, while introducing hierarchical and X model algorithms, binary and x hierarchical model, the concept of deep face recognition structure has been addressed and some of the latest algorithms produced for this purpose. In the end, some of the most important applications of facial diagnostic systems have been studied. The purpose of this article is to introduce and express deep learning algorithms in face recognition and expression of existing challenges.
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