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자연 재해로 인하여 낙과된 무채색 배 봉지 검출

Detection of Fallen Pear Bags caused by Natural Disaster

  • 최두현 (경북대학교 IT대학 전자공학부)
  • Choi, Doo-Hyun (School of Electronics Engineering, Kyungpook National University)
  • 투고 : 2015.10.29
  • 심사 : 2015.12.30
  • 발행 : 2016.01.25

초록

본 논문에서는 집중호우, 태풍, 허리케인과 같은 자연재해로 인한 낙과된 배 봉지를 자동으로 검출할 수 있는 알고리즘을 구현하였다. 검출 대상인 배 봉지는 글자가 인쇄된 회색 계열로, 수출용 배를 대량으로 생산하는 상주와 나주의 대규모 농원들에서 주로 사용한다. 제안한 알고리즘은 먼저 영상에서 관심영역을 설정하고, 설정한 관심 영역에 대해 유채색 영역을 제거한 후 형태학적 연산을 사용하여 잡음이나 이상 영역을 제거하여 낙과 영역을 검출한다. 이 낙과 영역을 분석하고 계수하여 낙과 피해 규모를 산정한다. 실험영상으로는 2014년 상주와 나주 배농원에서 촬영한 영상을 사용하였다. 제안한 기법은 실험영상에 대해 90% 이상의 검출 성능을 얻었으며, 알고리즘 구성이 간단해서 실시간 하드웨어 적용 및 모바일 디바이스를 활용한 구현도 가능하다.

A detection algorithm of fallen pear bags caused by natural disaster like heavy rain, typhoon, hurricane, etc. is presented in this paper. The algorithm is developed for the gray pear bags with printed characters which are widely used at pear farms at Sangju and Naju producing large quantity of pears for export. It sets a region of interest (ROI) at first and then eliminates the regions having chromatic color in ROI. Morphological operation and prior information are used to eliminate small noises and several unusual regions and finally the regions of fallen pear bags are remained. The remained regions are analyzed and counted to estimate the scale of damage. Test images are consisted of the images taken at pear farms of Sangju and Naju at 2014. Experimental result shows that the detection rate of pear bags is more than 90% and also the proposed system can be implemented in real-time using hand-held devices because of its simple and parallel architecture.

키워드

참고문헌

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