Edge Linking by Ellipsoidal Clustering

Visvanathan Ramesh; Robert M. Haralick

doi:10.1117/12.969730

1 March 1990 Edge Linking by Ellipsoidal Clustering

Visvanathan Ramesh, Robert M. Haralick

Proceedings Volume 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques; (1990) https://doi.org/10.1117/12.969730
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

Abstract

This paper discusses a method for edge linking using an ellipsoidal clustering technique. The ellipsoidal clustering technique assumes that each data point is an ellipsoid with a mean and covariance matrix and generates a decision tree which partitions the sample ellipsoids into clusters. The problem of edge linking can be visualized as a clustering process. By assuming the properties of each edge pixel to be components of the data vector, pixels having similar properties are clustered together and pixels in the same cluster are linked together. The edge data is obtained using the facet model based edge detector and the calculation of the property vectors and the covariance matrices of the edge pixels is also computed from the facet edge detector output. The performance of the clustering algorithm is evaluated by computing the average clustering error and the relationships between the clustering threshold, the noise level and the clustering error are outlined.

Citation Download Citation

Visvanathan Ramesh and Robert M. Haralick "Edge Linking by Ellipsoidal Clustering", Proc. SPIE 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, (1 March 1990); https://doi.org/10.1117/12.969730

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