Shape characterization using laws of texture energy measures facilitating retrieval

References

• Hu D, Shang L, Zhu Z, et al. Shape matching and object recognition using common base triangle area. IET Comput Vis. 2015;9:769–778. doi: 10.1049/iet-cvi.2014.0409
   Web of Science ®Google Scholar
• Zhou Y, Liu J, Bai X. Research and perspective on shape matching. Acta Autom Sin. 2012;38:889. doi: 10.3724/SP.J.1004.2012.00889
   Google Scholar
• Shu X, Wu X-JX. A novel contour descriptor for 2D shape matching and its application to image retrieval. Image Vis Comput. 2011;29:286–294. doi: 10.1016/j.imavis.2010.11.001
   Web of Science ®Google Scholar
• Attalla E, Siy P. Robust shape similarity retrieval based on contour segmentation polygonal multiresolution and elastic matching. Pattern Recognit. 2005;38:2229–2241. doi: 10.1016/j.patcog.2005.02.009
   Web of Science ®Google Scholar
• Ling H, Okada K. An efficient earth mover’s distance algorithm for robust histogram comparison. IEEE Trans Pattern Anal. 2007;29:840–853. doi: 10.1109/TPAMI.2007.1058
   PubMed Web of Science ®Google Scholar
• Belongie S, Malik J, Puzicha J. Shape matching and object recognition using shape contexts. IEEE Trans Pattern Anal Mach Intell. 2002;24:509–522. doi: 10.1109/34.993558
   Web of Science ®Google Scholar
• Ling H, Jacobs D. Shape classification using the inner-distance. IEEE Trans Pattern Anal. 2007;29:286–299. doi: 10.1109/TPAMI.2007.41
   PubMed Web of Science ®Google Scholar
• Alajlan N, Kamel MS, Freeman GH. Geometry-based image retrieval in binary image databases. IEEE Trans. 2008;30:1003–1013.
   Google Scholar
• El Rube I, Alajlan N, Kamel M. Robust multiscale triangle-area representation for 2D shapes. IEEE International Conference on Image Processing; 2005.
   Google Scholar
• Alajlan N, El Rube I, Kamel MMS, et al. Shape retrieval using triangle-area representation and dynamic space warping. Pattern Recognit. 2007;40:1911–1920. doi: 10.1016/j.patcog.2006.12.005
   Web of Science ®Google Scholar
• Temlyakov A, Munsell B. Two perceptually motivated strategies for shape classification. IEEE Computer Society Conference on Computer Vision and Pattern Recognition; 2010.
   Google Scholar
• Matsuda Y, Ogawa M, Yano M. Shape retrieval with geometrically characterized contour partitions. IEEE Access. 2015;3:1161–1178. doi: 10.1109/ACCESS.2015.2451627
   Web of Science ®Google Scholar
• Yang J, Wang H, Yuan J, et al. Invariant multi-scale descriptor for shape representation, matching and retrieval. Comput Vis Image Underst. 2016;145:43–58. doi: 10.1016/j.cviu.2016.01.005
   Web of Science ®Google Scholar
• Dash S, Jena U. Texture classification using steerable pyramid based laws’ masks. J Electr Syst Inf. 2016;4:185–197.
   Google Scholar
• Howarth P, Rüger S. Evaluation of texture features for content-based image retrieval. Int Conf Image Video; 2004.
   Google Scholar
• Acar E, Özerdem M. An iris recognition system by laws texture energy measure based k-NN classifier. Signal Processing and Communications Applications Conference (SIU); 2013.
   Google Scholar
• Setiawan A, Wesley J, Purnama Y. Mammogram classification using law’s texture energy measure and neural networks. Proc Comput Sci. 2015;59:92–97. doi: 10.1016/j.procs.2015.07.341
   Google Scholar
• Ion A, Artner NM, Peyré G, et al. Matching 2D and 3D articulated shapes using the eccentricity transform. Comput Vis Image Underst. 2011;115:817–834. doi: 10.1016/j.cviu.2011.02.006
   Web of Science ®Google Scholar
• Kaothanthong N, Chun J, Tokuyama T. Distance interior ratio: a new shape signature for 2D shape retrieval. Pattern Recognition Letters. [Internet]. 2016 [cited 2017 Jul 7]; 78:14–21. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0167865516300332
   Google Scholar
• Felzenszwalb P, Schwartz J. Hierarchical matching of deformable shapes. IEEE Conference on Computer Vision and Pattern Recognition; 2007.
   Google Scholar
• Wang J, Bai X, You X, et al. Shape matching and classification using height functions. Pattern Recognit Lett. 2012;33:134–143. doi: 10.1016/j.patrec.2011.09.042
   Web of Science ®Google Scholar
• Bai X, Rao C, Wang X. Shape vocabulary: a robust and efficient shape representation for shape matching. IEEE Trans Image Process. 2014;23:3935–3949. doi: 10.1109/TIP.2014.2336542
   PubMed Web of Science ®Google Scholar
• Bai X, Latecki L. Path similarity skeleton graph matching. IEEE Trans Pattern Anal. 2008;30:1282–1292. doi: 10.1109/TPAMI.2007.70769
   PubMed Web of Science ®Google Scholar
• Ling H, Yang X, Latecki LJ. Balancing deformability and discriminability for shape matching. Berlin: Springer; 2010; p. 411–424.
   Google Scholar
• Xiang Bai X, Xingwei Yang X, Latecki LJ, et al. Learning context-sensitive shape similarity by graph transduction. IEEE Trans Pattern Anal Mach Intell. 2010;32:861–874. doi: 10.1109/TPAMI.2009.85
   PubMed Web of Science ®Google Scholar