Adaptive Window Selection for Non-uniform Lighting Image Thresholding

Q4 Computer Science
Tapaswini Pattnaik, P. Kanungo
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引用次数: 0

Abstract

Selection of appropriate size of windows or subimages is the most important step for thresholding images with non-uniform lighting. In this paper, a novel criteria function is developed to partition images into different size of sub images appropriate for thresholding. After the partitioning, each subimage is segmented by Otsu’s thresholding approaches. The performance of the proposed method is validated on benchmark test images with different degree of uneven lighting. Based on the qualitative and quantitative measures, the  proposed method is fully automatic, fast and efficient in comparison to many landmark approaches.
非均匀光照图像阈值的自适应窗口选择
选择合适大小的窗口或子图像是对光照不均匀的图像进行阈值分割的最重要步骤。本文提出了一种新的准则函数,将图像划分为适合阈值分割的不同大小的子图像。分割后,使用Otsu的阈值分割方法对每个子图像进行分割。在不同光照不均匀程度的基准测试图像上验证了该方法的性能。基于定性和定量的方法,与许多标志性方法相比,该方法具有全自动、快速和高效的特点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Electronic Letters on Computer Vision and Image Analysis
Electronic Letters on Computer Vision and Image Analysis Computer Science-Computer Vision and Pattern Recognition
CiteScore
2.50
自引率
0.00%
发文量
19
审稿时长
12 weeks
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