An evaluation criterion for edge detection techniques in noisy images
| Autor: | Francisco L. Valverde, Robert M. Nishikawa, Nicolás Guil, Kunio Doi, José Muñoz |
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| Rok vydání: | 2002 |
| Předmět: |
Similarity (geometry)
Noise measurement Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-space segmentation Pattern recognition Image segmentation Edge detection Computer Science::Computer Vision and Pattern Recognition Pattern recognition (psychology) Segmentation Computer vision Noise (video) Artificial intelligence business |
| Zdroj: | ICIP (1) Scopus-Elsevier |
| DOI: | 10.1109/icip.2001.959158 |
| Popis: | Segmentation in noisy images is an important and difficult problem in pattern recognition. Edge detection is a crucial step in this process. Current subjective and objective methods for evaluation and comparison of segmentation techniques are inadequate or not applicable to edge detection techniques. A general framework for segmentation evaluation in noisy images is introduced after a brief review of previous work. Several measures based on similarity between true and result segmented images are defined. These measures are, then, combined in a unique criterion as a proposed global measure of performance. The results indicate that this global measure can be helpful in the evaluation and comparison of segmentation techniques applied to noisy images. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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