Shape Analysis

CVGResearch Home 3D Reconstruction Texture Analysis Shape Analysis Segmentation Recognition Fractal Graphics Members				Shape Analysis Different objects typically posses distinctive shapes. This makes shape an important discriminant feature for object description and recognition. Some shapes are instinctively planar such as those of alphabets and words while many others are 3D in nature. Shape analysis is key to many applications such as character recognition, symbol classification and retrieval, object recognition and retrieval.
				Invariant Description and Retrieval of Planar Shapes Using Radon Composite Features. Yun Wen Chen and Yan Qiu Chen. IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 56, NO. 10, OCTOBER 2008
				Abstract. This paper proposes a novel feature-based invariant descriptor termed Radon composite features (RCFs) for planar shapes. Instead of analyzing shapes directly in the spatial domain, some shape features are extracted from the Radon transform plane using statistical and spectral analysis. The proposed method overcomes the drawbacks of existing shape representation techniques since it accomplishes the invariances to common geometrical transformations without any normalization process, which usually causes inaccuracies. A novel hierarchical strategy with RCFs can achieve low complexity and coarse-to-fine retrieval, and perform accurately when retrieving shapes, while remaining robust against variations. Experiments demonstrate that RCF provides a higher degree of discrimination as compared with several state-of-the-art approaches.

				An Invariant Shape Representation: Interior Angle Chain. Bin Wang, Yan Qiu Chen. International Journal of Pattern Recognition and Artificial Intelligence, Vol. 21, No. 3, pp 543–559, 2007
				Abstract. This paper proposes a novel shape representation scheme — Interior Angle Chain (IAC) — which is invariant to translation, rotation and scaling. The proposed method first approximates the contour of a planar shape with an equilateral polygon and then makes a representation using the polygon’s interior angle chain. The difference between two shapes is measured by the distance between their IAC’s. An algorithm to obtain equilateral polygon approximation and its associated IAC is proposed in this paper. The proposed shape representation scheme has been tested on two benchmarks and applied to lake recognition in SAR (Synthetic Aperture Radar) images. The results show that IAC is an effective shape representation scheme.

				Connected Equi-Length Line Segments for Curve and Structure Matching. Yu Zhao, Yan Qiu Chen. International Journal of Pattern Recognition and Artificial Intelligence, Vol. 18, No. 6, pp 1019 - 1037, 2004
				Abstract. This paper deals with the problem of matching curves and structures extracted from 2D images that are subject to translation, rotation, scaling and other geometric transformations. We present in this paper a novel approach, Connected Equi-Length Line Segments (CELLS), for curve representation and matching. In our framework, a curve is represented by a number of connected equi-length line segments and a new matrix called Orientation Difference Matrix (ODM) is constructed for the curve, which reflects the distribution of the rest of the line segments with respect to the current one using orientation differences between them. The representation is invariant to rotation, scaling and translation. The problem of structure matching is also considered in this paper and is solved based on CELLS. The matching of structures is performed by (1) detecting tri-junctions and quad-junctions on the structures, (2) representing each arch using CELLS. A practical use of the proposed approach is demonstrated by registering a SAR image of a certain area to a map.