Thresholding technique with adaptive window selection for uneven lighting image

Authors:
Qingming Huang;Wen Gao;Wenjian Cai
Affiliations:
Joint R&D Lab, Graduate School, Chinese Academy of Sciences, P.O. Box 2704, Beijing 100080, PR China;Joint R&D Lab, Graduate School, Chinese Academy of Sciences, P.O. Box 2704, Beijing 100080, PR China;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
Venue:
Pattern Recognition Letters
Year:
2005

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Abstract

By adaptively selecting image window size based on the pyramid data structure manipulation of Lorentz information measure, a new technique for image thresholding is proposed. The advantage of this technique is its effectiveness in eliminating both uneven lighting disturbance and ghost objects. When applied to Otsu's thresholding approach, it can provide accurate result under uneven lighting disturbance while using Otsu's method alone cannot. Experimental results show the effectiveness of this method.