Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Binarization Method of Night Illumination Image with Low Information Loss Using Fuzzy Logic

퍼지논리를 이용하여 정보손실이 적은 야간조명 영상의 이진화 방법 연구

  • Lee, Ho Chang (Research Institute Computers, Information and Communication, Pusan National University)
  • Received : 2019.04.12
  • Accepted : 2019.04.29
  • Published : 2019.05.31
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Abstract

This study suggests a binarization method that minimizes information loss for night illumination images. The object of the night illumination image is an image which is not focused due to the influence of illumination and is not identifiable. Also, the image has a brightness area in only a part of the brightness histogram. So the existing simple binarization method is hard to get good results. The proposed binarization method uses image segmentation method and image merging method. In the stepwise divided blocks, we divide into two regions using the triangular type of fuzzy logic. The value 0 of the membership degree is binarized at the present step, and the value of the membership degree 1 is binarized after the next step. Experimental results show that night illumination images with minimal loss of information can be obtained in a dark area brightness range.

본 연구는 야간조명 영상에 대한 정보손실을 최소화하는 이진화 방법을 제안한다. 야간조명 영상의 대상은 조명의 영향으로 초점이 맞지 않으며 식별이 불가능한 영상이다. 또한 영상은 명도 히스토그램에서 일부 영역에만 치우친 명도 영역을 가지고 있다. 그래서 기존의 단순한 이진화 방법은 좋은 결과를 얻기에는 힘들다. 제안한 이진화 방법은 영상을 분할하는 방법과 영상 합병 방법을 사용한다. 단계별로 분할된 블록 내에서는 삼각형 타입의 퍼지논리를 이용하여 두 영역으로 구분한다. 소속도의 값이 0은 현 단계에서 이진화하며 소속도의 값이 1은 다음 단계 이후에 이진화를 한다. 실험 결과는 검은색부분에 밀집된 명도 영역에서 정보손실이 최소화된 야간조명 영상을 취득할 수 있었다.

Keywords

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Fig. 1 Image Histogram

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Fig. 2 Image Divide․Merger process

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Fig. 3 Application inTtriangles

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Fig. 4 Processing Area of Triangle

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Fig. 5 Original Image for Experiment

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Fig. 6 Step-by-step Image

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Fig. 7 Experiment Result of Person Image

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Fig. 8 Experiment Result of Cat Image

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Fig. 9 Experiment Result of Restaurant Image

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Fig. 10 Histogram of the Original Image

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Fig. 11 Triangle Shape by Step

Table. 1 Data for the Original Image

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