19 بهمن 1401
سكينه اسدي اميري

سکینه اسدی امیری

مرتبه علمی: استادیار
نشانی: دانشگاه مازندران
تحصیلات: دکترای تخصصی / مهندسی کامپیوتر
تلفن: 011-35302901
دانشکده: دانشکده مهندسی و فناوری

مشخصات پژوهش

عنوان Robust Face Recognition Under Illumination Changes and Pose Variations
نوع پژوهش مقاله چاپ شده
کلیدواژه‌ها
Face Recognition, PCA, SIFT Descriptor, Feature Extraction.
مجله journal of computing and security
شناسه DOI 10.22108/jcs.2018.110882
پژوهشگران حمید حسن پور (نفر اول) ، امید کهنسال (نفر دوم) ، سکینه اسدی امیری (نفر سوم)

چکیده

There are many applications for face recognition. Due to illumination changes, and pose variations of facial images, face recognition is often a challenging and a complicated process. In this paper, we propose an e ective and robust face recognition method. Firstly, we select those areas from the face (such as eyes, nose, and mouth), which are more informative in face recognition. Then SIFT (Scale Invariant Feature Transform) descriptor is utilized for feature extraction from the selected areas. SIFT descriptor detects keypoints in the image and describes each keypoint with a feature vector with length 128. To speed up the proposed method, PCA (Principal Component Analysis) is applied on the SIFT feature vector to reduce the vector's length. Finally, Kepenekci matching method is used to assess similarity between the images. The proposed method is evaluated on the ORL, Extended Yale B, and FEI databases. Results show considerable performance of the proposed face recognition method in comparison with several state-of-the-arts.