Image Analysis Using Mathematical Morphology
IEEE Transactions on Pattern Analysis and Machine Intelligence
Invariant Image Recognition by Zernike Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Partial Shape Classification Using Contour Matching in Distance Transformation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Representation by Multiscale Contour Approximation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of moment-based techniques for unoccluded object representation and recognition
CVGIP: Graphical Models and Image Processing
Visual Image Retrieval by Elastic Matching of User Sketches
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape representation and recognition from multiscale curvature
Computer Vision and Image Understanding
Recognition of Shapes by Editing Their Shock Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Invariant matching and identification of curves using B-splines curve representation
IEEE Transactions on Image Processing
A novel contour descriptor for 2D shape matching and its application to image retrieval
Image and Vision Computing
Matching 2D and 3D articulated shapes using the eccentricity transform
Computer Vision and Image Understanding
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This paper proposes a new approach called rolling penetrate descriptor for shape description. It combines the advantage of the contour-based and the region-based methods, and provides an unified scheme to handle various shapes. The main process of the proposed method is to use a set of scanning lines that rotate around the shape centroid to collect information. During the rotating process, three feature functions are computed to reveal the inner structures of the candidate shape. The proposed method is very flexible and can be adapted for certain applications, while the scanning process serves as a framework. The rolling penetrate descriptor method is tested on several data sets with variations including common geometrical transform, noise, distortion and occlusion. Experimental results demonstrate that the proposed approach has strong capability in handling a variety of shapes.