ON SUPERVISED METRICS FOR SHAPE SEGMENTATION

被引：0

作者：

Garcia Gonzalez, Dibet ^{[1
]}

Garcia Silvente, Miguel ^{[2
]}

机构：

[1] Ciego de Avila Univ, Adv Comp Sci Technol Ctr, Moron St, Ciego De Avila, Cuba

[2] Univ Granada, Comp Sci & Artificial Intelligence Dept, Granada, Spain

来源：

BIOSIGNALS 2010: PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON BIO-INSPIRED SYSTEMS AND SIGNAL PROCESSING | 2010年

关键词：

Segmentation evaluation; Metrics; Comparison functions; Segmentation algorithms; Thresholding; Ranking; IMAGE SEGMENTATION; PERFORMANCE EVALUATION; ACCURACY; REGION;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Segmentation is one of the most critical steps in image analysis. Also, the quantification of the error commited during this step is not a straightforward task. In this work, the performance of some comparison function or metrics are studied, when just one object appears in the analyzed regions. We develop a method for rank many validation measures of segmentation algorithms. It is based on thresholding a test image with a range of threshold and to find the middle threshold value when the performance measure is minimum or maximum. The performance is plotted and the first derivate is employed in the ranking construction. We have determined that RDE and MHD are two performance measures that show the best results (both are the most selective).

引用

页码：468 / 473

页数：6

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