DYNAMIC MEASUREMENT OF COMPUTER GENERATED IMAGE SEGMENTATIONS
DYNAMIC MEASUREMENT OF COMPUTER GENERATED IMAGE SEGMENTATIONS
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DOI：
10.1109/tpami.1985.4767640
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发表时间：
1985-01-01
影响因子：
23.6
通讯作者：
NAZIF, AM
中科院分区：
文献类型：
--
作者：
LEVINE, MD;NAZIF, AM
本文介绍了一种通用的图像分割算法的性能测量方案。实时运行的性能参数将该方法与依赖于正确分割的先验知识的先前方法区分开来。一个低层次的，上下文无关的定义的分割是用来获得一组优化标准，用于评估性能。每个区域内的均匀性和相邻区域之间的对比度用作区域分析的参数。线之间的对比度和它们之间的连通性代表线分析的度量。纹理是通过引入作为区域和线条组的关注区域来描述的。然后分别测量每个区域的性能参数。这种方法的有用性在于能够根据不同区域的不同特征来调整系统的策略。该反馈路径提供了更有效和无错误处理的手段。不同属性的区域的结果显示了用于动态策略设置的测量的多样性。
This paper introduces a general purpose performance measurement scheme for image segmentation algorithms. Performance parameters that function in real-time distinguish this method from previous approaches that depended on an a priori knowledge of the correct segmentation. A low level, context independent definition of segmentation is used to obtain a set of optimization criteria for evaluating performance. Uniformity within each region and contrast between adjacent regions serve as parameters for region analysis. Contrast across lines and connectivity between them represent measures for line analysis. Texture is depicted by the introduction of focus of attention areas as groups of regions and lines. The performance parameters are then measured separately for each area. The usefulness of this approach lies in the ability to adjust the strategy of a system according to the varying characteristics of different areas. This feedback path provides the means for more efficient and error-free processing. Results from areas with dissimilar properties show a diversity in the measurements that is utilized for dynamic strategy setting.