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블록 동질성 분할을 이용한 화재불꽃 영역 추출에 관한 연구

A Study on the Fire Flame Region Extraction Using Block Homogeneity Segmentation

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In this study, we propose a new Fire Flame Region Extraction using Block Homogeneity Segmentation method of the Fire Image with irregular texture and various colors. It is generally assumed that fire flame extraction plays a very important role. The Color Image with fire flame is divided into blocks and edge strength for each block is computed by using modified color histogram intersection method that has been developed to differentiate object boundaries from irregular texture boundaries effectively. The block homogeneity is designed to have the higher value in the center of region with the homeogenous colors or texture while to have lower value near region boundaries. The image represented by the block homogeneity is gray scale image and watershed transformation technique is used to generate closed boundary for each region. As the watershed transform generally results in over-segmentation, region merging based on common boundary strength is followed. The proposed method can be applied quickly and effectively to the initial response of fire

Abstract

In this study, we propose a new Fire Flame Region Extraction using Block Homogeneity Segmentation method of the Fire Image with irregular texture and various colors. It is generally assumed that fire flame extraction plays a very important role. The Color Image with fire flame is divided into blocks and edge strength for each block is computed by using modified color histogram intersection method that has been developed to differentiate object boundaries from irregular texture boundaries effectively. The block homogeneity is designed to have the higher value in the center of region with the homeogenous colors or texture while to have lower value near region boundaries. The image represented by the block homogeneity is gray scale image and watershed transformation technique is used to generate closed boundary for each region. As the watershed transform generally results in over-segmentation, region merging based on common boundary strength is followed. The proposed method can be applied quickly and effectively to the initial response of fire

참고문헌 (9)

  1. 제1차 화재안전정책 기본계획, 2017~2021, "국민안전처", ~
  2. 제4차 산업혁명시대의 ICT 융합형 재난안전 R&D 발전방향, "한국과학기술기획평가원", ~, pp.ISSUE PAPER 2016(06) (2016)
  3. B.C. Ko, "Fire Detection Based on Vision Sensor and Support Vector Machines", Fire Safety Journal, 41(3), pp.322~329 (2009)
  4. Giuseppe Marbach, "An Image Processing Technique for Fire Detection in Video Images", Fire Safety Journal, 41(4), pp.285~289 (2006)
  5. Turgay Celik, "Fire Detection in Video Sequences Using a Generic Color Model", Fire Safety Journal, 44(2), pp.147~158 (2009)
  6. Vincent, "Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations", IEEE Trans. PAMI, pp.583~597 (1999)
  7. Purgathofer, W, "A Simple method for Color Quantization: Octree Quantization", Magenat-Thalmann and Thalmann, pp.219~231 (1988)
  8. Purgathofer, W, "Graphics Gems", pp.287~293 (1990)
  9. W. Y. Ma, "NETRA: A Toolbox for Navigating Large Image Databases", Proc. IEEE International Conference on Image Processing, 1, pp.568~571 (1997)

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