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6 July 2015Image thresholding based on Adjusted Rand Index
This paper proposes a new image thresholding method by integrating Multi-scale Gradient Multiplication (MGM) transformation and Adjusted Rand Index (ARI). The proposed method evaluates the optimal threshold by computing the accumulation similarity between two image collections from the perspective of global spatial attributes of images. One of the image collections are obtained by binarizing the original gray level image with each possible gray level. The others are the reference images, produced by binarizing MGM image. The MGM image is the result of applying MGM transformation to the original image. ARI is a similarity measurement in statistics, particularly in data clustering, which can be readily computed based on two image matrices. To be more accurate, the optimal threshold is determined by maximizing the accumulation similarity of ARI. Comparisons with three well established thresholding methods are depicted for numbers of real-world images. Experiment results demonstrate the effectiveness and robustness of the proposed method.
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Lulu Fang, Yaobin Zou, Fangmin Dong, Bangjun Lei, Shuifa Sun, "Image thresholding based on Adjusted Rand Index," Proc. SPIE 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015), 96310F (6 July 2015); https://doi.org/10.1117/12.2197014