Image-Based Face Recognition

Zhao, Wenyi; Chellappa, Rama

doi:10.1201/9780203910962.ch13

Cited by 39 publications

(32 citation statements)

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Section: 서론 조명의 변화 상호 겹침에 따른 차단 지나친 조명에unclassified

“…최근 영상인식이나 정합, 그리고 영상 신호의 전송을 위해 획득된 영상의 화질개선에 대한 요구가 높아지고 있다 [1][2][3][4][5]. 이를 위한 기존의 히스토 그램 평활화(conventional histogram equalization : CHE)는 가장 널리 이용되는 화질개선 기법으로 히스 토그램에 의한 누적분포함수(cumulative density function : CDF)의 변환함수에 따라 명암도의 동적영역 을 재조정하는 공간영역 기법이다 [2][3][4][5][6][7][8][9]. 하지만 평활영 상의 밝기가 과도하게 변하는 문제점이 있으며, 이를 해결하기 위한 기법들에는 히스토그램의 대칭성이나 세밀한 부분의 향상 및 평활에 걸리는 시간 등에서 화 질 개선정도의 한계가 있어, 다양한 종류의 일반영상에 적용하기에는 제약이 있다 [6][7][8][9].…”

Section: 서론 조명의 변화 상호 겹침에 따른 차단 지나친 조명에unclassified

“…한편 영상인식에는 명암의 특징이나 세기를 고려한 기법으로 특징기반 접근(feature-based approach)법과 영상기반 접근(intensity-based approach)법이 널리 이 용되고 있다 [3][4][5]. 전자는 명암을 고려하지 않는 방법 으로 영상에서 공통적 속성을 제공하는 특징만을 찾아 인식에 이용하는 방법이다.…”

Section: 서론 조명의 변화 상호 겹침에 따른 차단 지나친 조명에unclassified

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Image Recognition Based on Nonlinear Equalization and Multidimensional Intensity Variation

Cho¹

2014

Journal of Korean Institute of Intelligent Systems

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This paper presents a hybrid recognition method, which is based on the nonlinear histogram equalization and the multidimensional intensity variation of an images. The nonlinear histogram equalization based on a adaptively modified function is applied to improve the quality by adjusting the brightness of the image. The multidimensional intensity variation by considering the a extent of 4-step changes in brightness between the adjacent pixels is also applied to reflect accurately the attributes of image. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to comprehensively measure the similarity between the images. The NCC is considered by the intensity variation of each 2-direction(x-axis and y-axis) image. The proposed method has been applied to the problem for recognizing the 50-face images of 40*40 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the histogram equalization, or the linear histogram equalization, respectively.

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Section: 서론 조명의 변화 상호 겹침에 따른 차단 지나친 조명에unclassified

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Image Recognition Based on Nonlinear Equalization and Multidimensional Intensity Variation

Cho¹

2014

Journal of Korean Institute of Intelligent Systems

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“…Recovering a 3D model from 2D images is a difficult task. Two types of approaches have been around: [22][23][24][25] one using model-based and the other using the imagebased approach. Explicit [26,27] knowledge of prior 3D models have been used in Model-based approaches.…”

Section: Introductionmentioning

confidence: 99%

A Novel Permutation Based Approach for Effective and Efficient Representation of Face Images under Varying Illuminations

Shylaja¹,

Murthy²,

Natarajan³

2013

IJACSA

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Abstract-Paramount importance for an automated face recognition system is the ability to enhance discriminatory power with a low-dimensional feature representation. Keeping this as a focal point, we present a novel approach for face recognition by formulating the problem of face tagging in terms of permutation. Using a fundamental concept that, dominant pixels of a person will remain dominant under varying illuminations, we develop a Permutation Matrix (PM) based approach for representing face images. The proposed method is extensively evaluated on several benchmark databases under different exemplary evaluation protocols reported in the literature. Experimental results and comparative study with state-of-the-art methods suggest that the proposed approach provides a better representation of face, thereby achieving higher efficacy and lower error rates.

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“…Face recognition rely on several techniques which have grown in maturity these last years [1] . A current challenge in face recognition is to improve existing algorithms to have better results and extract more reliable information about face expression and different people.…”

Section: Introductionmentioning

confidence: 99%

Extraction and fusion of spectral parameters for face recognition

et al. 2011

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Many methods have been developed in image processing for face recognition, especially in recent years with the increase of biometric technologies. However, most of these techniques are used on grayscale images acquired in the visible range of the electromagnetic spectrum. The aims of our study are to improve existing tools and to develop new methods for face recognition. The techniques used take advantage of the different spectral ranges, the visible, optical infrared and thermal infrared, by either combining them or analyzing them separately in order to extract the most appropriate information for face recognition. We also verify the consistency of several keypoints extraction techniques in the Near Infrared (NIR) and in the Visible Spectrum.

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Image-Based Face Recognition

Cited by 39 publications

References 0 publications

Image Recognition Based on Nonlinear Equalization and Multidimensional Intensity Variation

Image Recognition Based on Nonlinear Equalization and Multidimensional Intensity Variation

A Novel Permutation Based Approach for Effective and Efficient Representation of Face Images under Varying Illuminations

Extraction and fusion of spectral parameters for face recognition

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