Earticle

초록

영어

The scarcity of automatic fire detection systems continues to be a problem that needs a serious attention in order to save human lives by preventing injuries and/or deaths. The newest innovations are continuing to use cameras and computer algorithms to analyze the visible effects of fire and its motion in their applications. As their approaches present some drawbacks when working in spatial domain, the main difficulty is still to identify objects if they do not occur at the expected position. In this paper, we present an improved fast and robust algorithm for detecting fire/smoke in a cluttered scene from a pair of cameras. The input images are first segmented according to a pre-determined disparity threshold map and the real-time disparities of fire. Binary image processing techniques are used to reject noise introduced into the segmented images through low-resolution disparity calculations which consequently can lead to the gain of clearer results. In order to reduce the false alarms, a new segmentation method used in this approach shows that segmented images using stereo-vision are more accurate than those segmented using color approach for the overall detection. The segmented images are then used for image feature extraction for a Fuzzy-neural network classifier to help the system to generate a warning in case fire/smoke is detected.

목차

Abstract
 1. Introduction
 2. Related Works
 3. Proposed Approach
 4. The algorithm
  4.1. Dataset and Preprocessing
 5. Stereo Setup and Segmentation Algorithm
  5.1. Disparity Threshold Map Determination
  5.2. Background Suppression
  5.3. On-line Morphological Operator Application for Object Enhancement
 6. Features Extraction
 7. Fuzzy Logic Based Fire Recognition
 8. Experiment results
 9. Conclusion
 Acknowledgements
 References

키워드

저자

• Jean Paul Dukuzumuremyi [ College of Information Science and Engineering, Central South University, Changsha, 410083, China ]
• Beiji Zou [ College of Information Science and Engineering, Central South University, Changsha, 410083, China ]
• Damien Hanyurwimfura [ College of Information Science and Engineering, Hunan University, Changsha, 410082, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605