Intensity Axis Of Symmetry Research Articles

The patchwork engine: image segmentation from shape symmetries

We propose blind segmentation of images into shape-related ‘patches’ based on pre-calculated local symmetries (Van Tonder, G.J. & Ejima, Y. (1999). (Forthcoming a) Flexible computation of shape symmetries. Submitted for publication) in shape boundary contours. First, lateral weights between all points in the boundary contour map are assigned analogous to Euclidean distance maps in watershed segmentation (Beucher, S. & Lantejoul, C. (1979). Use of watersheds in contour detection. Proceedings of the International Workshop on Image Processing, CCETT, Rennes, France.). Lateral weights are then used to: (1) extract local maxima in symmetries; (2) link maxima within locally enclosed boundary contours; and (3) reconstruct shape contours using symmetry maxima as ‘seeds’. The new model overcomes weaknesses of watershed segmentation. The new model closes gaps in relatively more solid image contours, but it is fundamentally different from methods based on contour interpolation (Grossberg, S., Mingolla, E. & Todorovć, D. (1989). A neural network architecture for pre-attentive vision, IEEE Transactions on Biomedical Engineering 36, 65–84; Heitger, F. & von der Heydt, R. (1993). A computational model of neural contour processing: figure-ground segregation and illusory contours. Proceedings of the Fourth International Conference on Computer Vision, IEEE Computer Society Press, Washington D.C. (pp. 32–40)). Images are segmented into shape-relevant color-by-number-like patches which compare well to related methods (Gauch, J. & Pizer, M. (1993). The intensity axis of symmetry and its application to image segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, 15 (8), 753–770; Ilg, W. & Ogniewicz, R. (1995). The application of Voronoi skeletons to perceptual grouping in line images, Proceedings of the 11th International Conference on Pattern Recognition, The Hague, The Netherlands, pp. 382–385; Zhu, S.C. & Yuille, A.L. (1996) FORMS: a flexible object recognition and modeling system, International Journal of Computer Vision, 20 (3), 187–212.). Two primitive operations, comparison and merging of patches, are proposed as drives for exposing more global shape contours from patches. We conclude that symmetry goes beyond abstract shape morphology: it can contribute to figure-ground segmentation in early vision and form part of primitive operations needed to create hypotheses of complex shape.

The intensity axis of symmetry and its application to image segmentation

The authors present the intensity axis of symmetry (IAS) method for describing the shape of structures in grey-scale images. They describe the spatial and intensity variations of the image simultaneously rather than by the usual two-step process of using intensity properties of the image to segment an image into regions and describing the spatial shape of these regions. The result is an image shape description that is useful for a number of computer vision applications. The method relies on minimizing an active surface functional that provides coherence in both the spatial and intensity dimensions while deforming into an axis of symmetry. Shape-based image segmentation is possible by identifying image regions associated with individual components of the IAS. The resulting image regions have geometric coherence and correspond well to visually meaningful objects in medical images. >