دانلود رایگان مقاله انگلیسی تشخیص چهره تحت تغییر عبارات و نورپردازی با استفاده از بهینه سازی ازدحام ذرات - الزویر 2018

عنوان فارسی
تشخیص چهره تحت تغییر عبارات و نورپردازی با استفاده از بهینه سازی ازدحام ذرات
عنوان انگلیسی
Face recognition under varying expressions and illumination using particle swarm optimization
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
15
سال انتشار
2018
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
نوع مقاله
ISI
نوع نگارش
مقالات پژوهشی (تحقیقاتی)
رفرنس
دارد
پایگاه
اسکوپوس
کد محصول
E10149
رشته های مرتبط با این مقاله
مهندسی کامپیوتر
گرایش های مرتبط با این مقاله
هوش مصنوعی
مجله
مجله علوم محاسباتی - Journal of Computational Science
دانشگاه
Department of Software Engineering - Foundation University Islamabad - Rawalpindi Campus - Pakistan
کلمات کلیدی
تشخیص چهره، حالت صورت، الگوی دودویی محلی، موجک، نورپردازی متغیر، بهینه سازی ذرات ریز
doi یا شناسه دیجیتال
https://doi.org/10.1016/j.jocs.2018.08.005
چکیده

Abstract


Social networks generate enormous amounts of visual data. Mining of such data in recommender systems is extremely important. User profiling is carried out in recommender systems to build the holistic persona of the user. Identification and grouping of images in these systems is carried out using face recognition. It is one of the most appropriate biometric features in such situations. Ever since the first use of face recognition in security and surveillance systems, researchers have developed many methods with improved accuracy. Face recognition under variant illumination is still an open issue and diverging facial expressions reduces the accuracy even further. State of the art methods produced an average accuracy of 90%.In this study, a computationally intelligent and efficient method based on particle swarm optimization (PSO) is developed. It utilizes the features extracted from texture and wavelet domain. Discrete Wavelet Transform provides the advantage of extracting relevant features and thereby reducing computational time and an increase in recognition accuracy rate. We apply particle swarm optimization technique to select informative wavelet sub-band. Furthermore, the proposed technique uses Discrete Fourier Transform to compensate the translational variance problem of the discrete wavelet transform. The proposed method has been tested on the CK, MMI and JAFFE databases. Experimental results are compared with existing techniques and the results indicate that the proposed technique is more robust to illumination and variation in expressions, average accuracy obtained over the CK, MMI and JAFFE datasets is 98.6%, 95.5%, and 98.8% respectively.

نتیجه گیری

Conclusion and Future Work


In this paper, the problem of face recognition under varying illumination and expressions has been investigated. A novel framework has been introduced to efficiently recognize the face images. LBP is used to preserve the local variations in the spatial domain. Discrete Wavelet Transform plays an important role in efficient feature extraction and multi-resolution analysis. PSO is utilized to select the optimal sub-band of DWT. The DWT translation variance problem is handled by applying DFT. The proposed technique provides good results and is also efficient for the images with variations in expression and illumination. Experiments on facial expression databases (CK, JAFFE, and MMI) demonstrate the effectiveness of proposed framework. Although proposed framework exhibits good performance, there is still room for improvement especially for the images captured in an unconstrained environment containing different types of noise.


بدون دیدگاه