An Approach Making the Shape Matching Techniques Robust to Noise

No abstract is available for this paper.

• Publication year

  2013

• Venue

  J. Multim. Process. Technol.

• Publication date

  Unknown publication date

• Fields of study

  Mathematics, Computer Science

• Identifiers

  No identifiers available.

• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Beyond Pairwise Shape Similarity Analysis

  2009cited by this paper
• Improving Shape Retrieval by Learning Graph Transduction

  2008cited by this paper
• Geometry-Based Image Retrieval in Binary Image Databases

  2008cited by this paper
• Robust symbolic representation for shape recognition and retrieval

  2008cited by this paper
• Hierarchical Matching of Deformable Shapes

  2007cited by this paper
• Shape Classification Using the Inner-Distance

  2007cited by this paper
• Integral Invariants for Shape Matching

  2006cited by this paper
• Probabilistic contour extraction using hierarchical shape representation

  2005cited by this paper
• Robust shape similarity retrieval based on contour segmentation polygonal multiresolution and elastic matching

  2005influential reference
• Efficient shape matching using shape contexts

  2005cited by this paper
• Matching and Retrieval of Distorted and Occluded Shapes Using Dynamic Programming

  2002cited by this paper
• Shape Matching and Object Recognition Using Shape Contexts

  2002cited by this paper
• Matching shapes

  2001cited by this paper
• Retrieval by Shape Similarity with Perceptual Distance and Effective Indexing

  2000cited by this paper
• Numerically Invariant Signature Curves

  1999cited by this paper
• Shape Representation and Recognition from Multiscale Curvature

  1997cited by this paper
• Determining the similarity of deformable shapes

  1995cited by this paper
• Invariant signatures for planar shape recognition under partial occlusion

  1992cited by this paper

• A Hybrid Approach for Shape Retrieval Using Genetic Algorithms and Approximate Distance

  2018cites this paper