An entropy-based objective evaluation method for image segmentation

Accurate image segmentation is important for many image, video and computer vision applications. Over the last few decades, many image segmentation methods have been proposed. However, the results of these segmentation methods are usually evaluated only visually, qualitatively, or indirectly by the effectiveness of the segmentation on the subsequent processing steps. Such methods are either subjective or tied to particular applications. They do not judge the performance of a segmentation method objectively, and cannot be used as a means to compare the performance of different segmentation techniques. A few quantitative evaluation methods have been proposed, but these early methods have been based entirely on empirical analysis and have no theoretical grounding. In this paper, we propose a novel objective segmentation evaluation method based on information theory. The new method uses entropy as the basis for measuring the uniformity of pixel characteristics (luminance is used in this p...

• Type: Conference
• Year: 2004
• Where: SPIESR
• Authors: Hui Zhang, Jason E. Fritts, Sally A. Goldman
• Keywords: Database, Image Segmentation, Segmentation Evaluation, Segmentation Method, SPIESR 2004