Journal of the Institute of Electronics Engineers of Korea CI (전자공학회논문지CI)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Face recognition rate comparison using Principal Component Analysis in Wavelet compression image

Wavelet 압축 영상에서 PCA를 이용한 얼굴 인식률 비교

  • Published : 2004.09.01
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Abstract

In this paper, we constructs face database by using wavelet comparison, and compare face recognition rate by using principle component analysis (Principal Component Analysis : PCA) algorithm. General face recognition method constructs database, and do face recognition by using normalized size. Proposed method changes image of normalized size (92${\times}$112) to 1 step, 2 step, 3 steps to wavelet compression and construct database. Input image did compression by wavelet and a face recognition experiment by PCA algorithm. As well as method that is proposed through an experiment reduces existing face image's information, the processing speed improved. Also, original image of proposed method showed recognition rate about 99.05%, 1 step 99.05%, 2 step 98.93%, 3 steps 98.54%, and showed that is possible to do face recognition constructing face database of large quantity.

본 논문에서는 웨이블릿 압축을 이용하여 얼굴 데이터베이스를 구축하고, 주성분 분석(Principal Component Analysis : PCA) 알고리듬을 이용하여 얼굴 인식률을 비교한다. 일반적인 얼굴인식 방법은 정규화된 크기를 이용하여 데이터베이스를 구축하고, 얼굴 인식을 한다. 제안된 방법은 정규화된 크기(92×112)의 영상을 웨이블릿 압축으로 1단계, 2단계, 3단계로 변환하고 데이터베이스를 구축한다. 입력 영상도 웨이블릿으로 압축하고 PCA 알고리듬으로 얼굴인식 실험을 하였다 실험을 통하여 제안된 방법은 기존 얼굴영상의 정보를 축소할 뿐만 아니라 처리속도도 향상되었다. 또한 제안된 방법은 원본 영상이 99.05%, 1단계 99.05%, 2단계 98.93%, 3단계 98.54% 정도의 인식률을 보였으며, 대량의 얼굴 데이터베이스를 구축하여 얼굴인식을 하는데 가능함을 보였다.

Keywords

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