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Object Detection in a Still FLIR Image using Intensity Ranking Feature  

Park Jae-Hee (Division of EE, Department of EECS, Korea Advanced Institute of Science and Technology)
Choi Hak-Hun (Division of EE, Department of EECS, Korea Advanced Institute of Science and Technology)
Kim Seong-Dae (Division of EE, Department of EECS, Korea Advanced Institute of Science and Technology)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.42, no.2, 2005 , pp. 37-48 More about this Journal
Abstract
In this paper, a new object detection method for FLIR images is proposed. The proposed method consists of intensity ranking feature and a classification algerian using the feature. The intensity ranking feature is a representation of an image, from which intensity distribution is regularized. Each object candidate region is classified as object or non-object by the proposed classification algorithm which is based on the intensity ranking similarity between the candidate and object training images. Using the proposed algorithm pixel-wise detection results can be obtained without any additional candidate selection algorithm. In experimental results, it is shown that the proposed ranking feature is appropriate for object detection in a FLIR image and some vehicle detection results in the situation of existing noise, scale variation, and rotation of the objects are presented.
Keywords
Intensity ranking; Object detection; FLIR image;
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Times Cited By KSCI : 1  (Citation Analysis)
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