A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition
SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
An Operator Which Locates Edges in Digitized Pictures
Journal of the ACM (JACM)
Boundary and Object Detection in Real World Images
Journal of the ACM (JACM)
Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discriminative Sparse Image Models for Class-Specific Edge Detection and Image Interpretation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Contour Detection and Hierarchical Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
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We have developed a robust statistical edge detection method by combining the ideas of Kundus method, in which the region segmentation of local area is used, and Fukuis method, in which a statistic evaluation value separability is used for edge extraction and also have developed a region segmentation method based on the global features like the statistics of the region. A new region segmentation method is developed by combining these two methods, in which the edge extraction method is used instead of the first step of region segmentation method. We obtained the almost same results as the ones of previous region segmentation method. The proposed one has some advantages because we are able to introduce a new conspicuity degree including a clear contrast value with the adjacent regions, a envelopment degree based on clear edge and so on without much difficulty and it will contribute to develop a further unification algorithm and a new feature extraction method for scene recognition.