Evaluation of Segmentation Quality via Adaptive Composition of Reference Segmentations
| Autor: | Xuanqin Mou, Bo Peng, Lei Zhang, Ming-Hsuan Yang |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Computer science
Segmentation-based object categorization business.industry Applied Mathematics ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-space segmentation 020206 networking & telecommunications Pattern recognition 02 engineering and technology Image segmentation Computational Theory and Mathematics Minimum spanning tree-based segmentation Image texture Artificial Intelligence Region growing 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Segmentation Computer vision Computer Vision and Pattern Recognition Artificial intelligence business Software |
| Zdroj: | IEEE Transactions on Pattern Analysis and Machine Intelligence. 39:1929-1941 |
| ISSN: | 2160-9292 0162-8828 |
| Popis: | Evaluating image segmentation quality is a critical step for generating desirable segmented output and comparing performance of algorithms, among others. However, automatic evaluation of segmented results is inherently challenging since image segmentation is an ill-posed problem. This paper presents a framework to evaluate segmentation quality using multiple labeled segmentations which are considered as references. For a segmentation to be evaluated, we adaptively compose a reference segmentation using multiple labeled segmentations, which locally matches the input segments while preserving structural consistency. The quality of a given segmentation is then measured by its distance to the composed reference. A new dataset of 200 images, where each one has 6 to 15 labeled segmentations, is developed for performance evaluation of image segmentation. Furthermore, to quantitatively compare the proposed segmentation evaluation algorithm with the state-of-the-art methods, a benchmark segmentation evaluation dataset is proposed. Extensive experiments are carried out to validate the proposed segmentation evaluation framework. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|