Image segmentation by local feature based clustering for understanding natural scene
Mutsuhiro Terauchi, Mitsuo Nagamachi, K. Ito, Toshio Tsuji · 2003
An approach to segmenting a gray-level image is presented and used to reconstruct the three-dimensional shape of unconstrained objects. In analyzing a natural image, the authors cannot utilize heuristic rules that constrain the degree of freedom of reconstruction of the scene. Therefore they use local feature-based clustering, which utilizes the local distribution of the features. This clustering is based on an image itself and is considered as object-oriented processing. The edge detection problem is discussed as an inverse problem to clustering. Clustering methods which utilize both lowest features (for all pixels) and the features a little higher up are discussed with respect to their ability for exact segmentation.>