Shape Analysis and Classification: Theory and Practice

By L. Costa, R. M. Cesar. 2000

870 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/a27cdd68542ef773931fba50a6c4315e9fad0d3d

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In Computer Vision and Pattern Recognition

Citations in the corpus

A Novel Method to Construct Taxonomy Electrical Appliances Based on Load Signaturesof (2007, methodology): “As introduced in [ 15 ]-[16], there are different methods for shape characterization and classification.”
Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification (2005, background): “The normal transformation is defined as [36]: v̂i = vi − µi σi where vi is the ith feature assumed by each pixel,µi is the average value of theith feature andσi is the associated standard deviation.”
Getting into Shape: An Empirical Comparison of Traditional Truss-Based Morphometric Methods with a Newer Geometric Method Applied to New World Cichlids (2003, background): “…about because of the availability of free, increasingly userfriendly software, and better resources that explain its components and utility (e.g., Rohlf & Bookstein 1990, Rohlf & Marcus 1993, Marcus et al. 1996, Dryden & Mardia 1998, Costa & Cesar 2000, Da Fontoura & Cesar 2000, Adams et al. 2003).”
Characterization of complex networks: A survey of measurements (2005, methodology): “Even when modeling networks, it is often necessary to compare the realizations of the model with real networks, which can be done by comparing respective measurements.”
Curvature Scale Space Representation: Theory, Applications, and MPEG-7 Standardization (2011, methodology): “of the accuracy of our method is the comprehensive work on I-D and 2-D approaches to numeric curvature est imation and their comparative performance assessment [75 , 76, 63] .”
Analyzing and modeling real-world phenomena with complex networks: a survey of applications (2007, neutral): “Image processing, analysis, characterization and classification are intrinsically related [204].”
Integration of enzyme activities into metabolic flux distributions by elementary mode analysis (2007, neutral): “Overview and community analysis Figure 1 presents a two-dimensional projection of the center of mass of the cortical areas together with their interconnections, obtained by principal component analysis [ 7 ].”