کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
383563 660826 2016 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multiscale morphology based illumination normalization with enhanced local textures for face recognition
ترجمه فارسی عنوان
عادی سازی روشنایی مبتنی بر مورفولوژی چندمقیاسی با بافت های محلی پیشرفته برای تشخیص چهره
کلمات کلیدی
تشخیص چهره؛ عادی سازی اشراق، اطلاعات بافت؛ تصویر هوش
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• A multiscale morphology based illumination normalization method is proposed.
• The proposed method is robust to various illumination conditions.
• Enhancing local texture information further improved the recognition performance.
• The proposed method showed improved performance on several databases.

A key challenge of face recognition is to obtain illumination invariant face images while preserving the discriminative features. The locations and shapes of small-scale features (e.g. eyebrows, eyes, nostrils, a mouth, etc.) are usually treated as key features for face recognition. However, it has also been observed that the local texture information of facial regions contains intrinsic facial features and needs to be enhanced to improve performance. To compensate for the illumination effects that appeared while extracting both the small-scale features and the texture information, we used multiscale morphological techniques. We used a generalized dynamic morphological quotient image (GDMQI) method based on Retinex theory and multiscale morphological closing to solve the artifact problem discussed in previous works. The proposed method consisted of two main steps: (i) illumination estimation and (ii) texture enhancement. The proposed method showed improved performance when using the CMU PIE, AR and Extended Yale-B databases.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 62, 15 November 2016, Pages 347–357
نویسندگان
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