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An Improved Double-Threshold Method Based on Gradient Histogram 被引量:2

An Improved Double-Threshold Method Based on Gradient Histogram
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摘要 This paper analyzes the characteristics of the output gradient histogram and shortages of several traditional automatic threshold methods in order to segment the gradient image better. Then an improved double-threshold method is proposed, which is combined with the method of maximum classes variance, estimating-area method and double-threshold method. This method can automatically select two different thresholds to segment gradient images. The computer simulation is performed on the traditional methods and this algorithm and proves that this method can get satisfying result. Key words gradient histogram image - threshold selection - double-threshold method - maximum classes variance method CLC number TP 391. 41 Foundation item: Supported by the National Nature Science Foundation of China (50099620) and the Project of Chenguang Plan in Wuhan (985003062)Biography: YANG Shen (1977-), female, Ph. D. candidate, research direction: multimedia information processing and network technology. This paper analyzes the characteristics of the output gradient histogram and shortages of several traditional automatic threshold methods in order to segment the gradient image better. Then an improved double-threshold method is proposed, which is combined with the method of maximum classes variance, estimating-area method and double-threshold method. This method can automatically select two different thresholds to segment gradient images. The computer simulation is performed on the traditional methods and this algorithm and proves that this method can get satisfying result. Key words gradient histogram image - threshold selection - double-threshold method - maximum classes variance method CLC number TP 391. 41 Foundation item: Supported by the National Nature Science Foundation of China (50099620) and the Project of Chenguang Plan in Wuhan (985003062)Biography: YANG Shen (1977-), female, Ph. D. candidate, research direction: multimedia information processing and network technology.
出处 《Wuhan University Journal of Natural Sciences》 CAS 2004年第4期473-476,共4页 武汉大学学报(自然科学英文版)
基金 SupportedbytheNationalNatureScienceFoundationofChina (50 0 9962 0 )andtheProjectofChenguangPlanin Wuhan(9850 0 30 62 )
关键词 gradient histogram image threshold selection double-threshold method maximum classes variance method gradient histogram image threshold selection double-threshold method maximum classes variance method
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  • 1王宗海(译),数字图像信号处理,1993年
  • 2吴敏金,华东师范大学学报,1992年,4期,62页
  • 3Fu S K,Pattern Recognit,1981年,13卷,1期,3页

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