کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
564806 875648 2007 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Image histogram thresholding based on multiobjective optimization
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
پیش نمایش صفحه اول مقاله
Image histogram thresholding based on multiobjective optimization
چکیده انگلیسی

The thresholding process based on the optimization of one criterion only does not work well for a lot of images. In many cases, even when equipped with the optimal value of the threshold of its single criterion, the thresholding program does not produce a satisfactory result. In this paper, we propose to use the multiobjective optimization approach to find the optimal thresholds of three criteria: the within-class criterion, the entropy and the overall probability of error criterion. In addition we develop a new variant of simulated annealing adapted to continuous problems to solve the Gaussian curve-fitting problem. Some examples of test images are presented to compare our segmentation method, based on the multiobjective optimization approach, with that of four competing methods: Otsu method, Gaussian curve fitting-based method, valley-emphasis-based method and two-dimensional Tsallis entropy-based method. From the viewpoints of visualization, object size and image contrast, our experimental results show that the thresholding method based on multiobjective optimization performs better than the competing methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing - Volume 87, Issue 11, November 2007, Pages 2516–2534
نویسندگان
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