Face Recognition through Combined SVD and LBP Features

نویسندگان

  • Rahul Kumar Mittal
  • Anupam Garg
چکیده

A number of global and local methods are available for the representation of face images, still no single approach is found to be suitable in most of the situations. As the information conveyed by these two feature sets, is different hence the techniques that combine the global and local features together are necessary to obtain the optimal results. In this paper, we have developed an approach to combine two feature sets obtained from SVD and LBP approaches. SVD approach is able to efficiently represent the global variations of face images whereas the LBP is one of the most useful descriptors to extract the local variation of face images. In order to analyse the effectiveness of the proposed approach obtained by the fusion of SVD and LBP approaches, various experiments have been carried out on ORL and Yale face databases. The proposed approach has also been compared to some existing techniques and from the detailed experiments it has been observed that the results obtained by the proposed method are far better than these approaches.

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

Facial Expression Recognition Based on Structural Changes in Facial Skin

Facial expressions are the most powerful and direct means of presenting human emotions and feelings and offer a window into a persons’ state of mind. In recent years, the study of facial expression and recognition has gained prominence; as industry and services are keen on expanding on the potential advantages of facial recognition technology. As machine vision and artificial intelligence advan...

متن کامل

A New Fast and Efficient HMM-Based Face Recognition System Using a 7-State HMM Along With SVD Coefficients

In this paper, a new Hidden Markov Model (HMM)-based face recognition system is proposed. As a novel point despite of five-state HMM used in pervious researches, we used 7-state HMM to cover more details. Indeed we add two new face regions, eyebrows and chin, to the model. As another novel point, we used a small number of quantized Singular Values Decomposition (SVD) coefficients as feature...

متن کامل

New Fusion of SVD and DCT-LBP for Face Recognition

In this paper, we proposed the fusion of two projection based face recognition algorithms: local binary Patterns in DCT domain and singular value decomposition (SVD) characterized by its simplicity and efficiently. Standard databases ORL are used to test the experimental results which prove that proposed system achieves more accurate face recognition as compared to individual method.

متن کامل

Face Recognition Based Rank Reduction SVD Approach

Standard face recognition algorithms that use standard feature extraction techniques always suffer from image performance degradation. Recently, singular value decomposition and low-rank matrix are applied in many applications,including pattern recognition and feature extraction. The main objective of this research is to design an efficient face recognition approach by combining many tech...

متن کامل

Fusing Shearlets and LBP Feature Sets for Face Recognition

To aim at the challenge of face recognition to uncontrolled situations, robust face recognition system requires to take into account different kinds of face appearance feature. However, most existing methods only use features of just one type. We show that integrating two of global and local representations, Shearlets features and local binary pattern (LBP), which gets better performance than e...

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:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014