A New Metric for Grey-Scale Image Comparison
International Journal of Computer Vision
Yet Another Survey on Image Segmentation: Region and Boundary Information Integration
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
How Dissimilar Are Two Grey-Scale Images?
Mustererkennung 1995, 17. DAGM-Symposium
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Detecting and ranking foreground regions in gray-level images
BVAI'05 Proceedings of the First international conference on Brain, Vision, and Artificial Intelligence
A case-based reasoning approach for detection of salient regions in images
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
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This paper proposes a novel grey-level image segmentation scheme employing case-based reasoning. Segmentation is accomplished by using the watershed transformation, which provides a partition of the image into regions whose contours closely fit those perceived by human users. Case-based reasoning is used to select the segmentation parameters involved in the segmentation algorithm by taking into account the features characterizing the current image. Preliminarily, a number of images are analyzed and the parameters producing the best segmentation for each image, found empirically, are recorded. These images are grouped to form relevant cases, where each case includes all images having similar image features, under the assumption that the same segmentation parameters will produce similarly good segmentation results for all images in the case.