Methodological improvement on local Gabor face recognition based on feature selection and enhanced Borda count

نویسندگان

  • Claudio A. Perez
  • Leonardo A. Cament
  • Luis E. Castillo
چکیده

Face recognition has awide range of possible applications in surveillance, human computer interfaces and marketing and advertising goods for selected customers according to age and gender. Because of the high classification rate and reduced computational time, one of the best methods for face recognition is based on Gabor jet feature extraction and Borda count classification. In this paper, we propose methodological improvements to increase face recognition rate by selection of Gabor jets using entropy and genetic algorithms. This selection of jets additionally allows faster processing for real-time face recognition. We also propose improvements in the Borda count classification through a weighted Borda count and a threshold to eliminate low score jets from the voting process to increase the face recognition rate. Combinations of Gabor jet selection and Borda count improvements are also proposed. We compare our results with those published in the literature to date and find significant improvements. Our best results on the FERET database are 99.8%, 99.5%, 89.2% and 86.8% recognition rates on the subsets Fb, Fc, Dup1 and Dup2, respectively. Compared to the best results published in the literature, the total number of recognition errors decreased from 163 to 112 (31%). We also tested the proposed method under illumination changes, occlusions with sunglasses and scarves and for small pose variations. Results on two different face databases (AR and Extended Yale B) with significant illumination changes showed over 90% recognition rate. The combination EJS–BTH–BIP reached 98% and 99% recognition rate in imageswith sunglasses and scarves from the AR database, respectively. The proposed method reached 93.5% recognition on faces with small pose variation of 251 rotation and 98.5% with 15% rotation in the FERET database. & 2010 Elsevier Ltd. All rights reserved.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

An Enhanced Algorithm for Thermal Face Recognition

In this paper, an enhanced thermal face recognition method, namely GMFB, is proposed. Initially, Gabor Jet Descriptor (GJD) is extracted from each thermal image with five scales and eight orientations. Then, the Modified Fisher (MF) criterion is implemented on the feature vector for every scale. Finally, the Borda count (BC) matching method is used to get higher matching score. Our proposed met...

متن کامل

تشخیص چهره با استفاده از PCA و فیلتر گابور

Methods for face recognition which are based on face structure are among techniques without supervision and produce unfavorable results in the presence of linear changes in images. PCA is a linear transform and a powerful tool for data analysis but does not produce good results for face recognition when there are non-linear changes resulting from changes in position, intensity and gesture in th...

متن کامل

Selection of Location, Frequency, and Orientation Parameters of 2D Gabor Wavelets for Face Recognition

In this paper, a two-level supervised feature selection algorithm for local feature-based face recognition is presented. In the first part, a genetic algorithm is used to determine the useful locations of the face region for recognition. 2D Gabor wavelet-based feature extractors are used for local image descriptors at these locations. In the second part, the most useful frequencies and orientat...

متن کامل

Gabor Feature Selection for Face Recognition

A discriminative and robust feature kernel enhanced informative Gabor feature is proposed in this paper for face recognition. Mutual information is applied to select a set of informative and non-redundant Gabor features, which are then further enhanced by Kernel methods for recognition. Compared with one of the top performing methods in the 2004 Face Verification Competition (FVC2004), our meth...

متن کامل

Textural feature based face recognition for single training images

A novel face recognition algorithm using single training face image is proposed. The algorithm is based on textural features extracted using the 2D log Gabor wavelet. These features are encoded into a binary pattern to form a face template which is used for matching. Experimental results show that on the colour FERET database the accuracy of the proposed algorithm is higher than the local featu...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Pattern Recognition

دوره 44  شماره 

صفحات  -

تاریخ انتشار 2011