Regular Articles

Polygonal approximation of contours based on the turning angle function

[+] Author Affiliations
Rangaraj M. Rangayyan

University of Calgary, Schulich School of Engineering, Department of Electrical and Computer Engineering, 2500 University Drive NW, Calgary, Alberta T2N 1N4 Canada

Denise Guliato

Universidade Federal de Uberlândia, Faculdade de Computação, Av. João Naves de Ávila, 2121, 38.400-902, Minas Gerais, Brazil

Juliano D. de Carvalho

Universidade Federal de Uberlândia, Faculdade de Computação, Av. João Naves de Ávila, 2121, 38.400-902, Minas Gerais, Brazil

Sérgio A. Santiago

Universidade Federal de Uberlândia, Faculdade de Computação, Av. João Naves de Ávila, 2121, 38.400-902, Minas Gerais, Brazil

J. Electron. Imaging. 17(2), 023016 (May 22, 2008). doi:10.1117/1.2920413
History: Received December 18, 2006; Revised October 01, 2007; Accepted October 14, 2007; Published May 22, 2008
Text Size: A A A

The turning angle function has been used as a signature to represent the shape of a given contour with the aim of analysis of shape and content-based image retrieval. We propose a method that uses the turning angle function to derive a polygonal model of the given contour in such a manner as to preserve the important details in the contour. The preservation of diagnostically significant features present in the contours of breast masses in mammograms are important to discriminate between benign masses and malignant tumors. To evaluate the practical utility of the proposed polygonal modeling method in terms of the efficiency in the classification of breast masses, we derive an index of spiculation SIPMTF and a measure of fractional concavity Fcc from the models obtained and compare the results with those provided by two methods proposed in previous related works. The features SIPMTF and Fcc were tested with a set of 111 contours, of which 65 are related to benign masses and 46 are related to malignant tumors. High classification accuracies of 0.93 with SIPMTF and 0.91 with Fcc were obtained, in terms of the area under the receiver operating characteristics curve, with a data compression of 0.067 on the average.

© 2008 SPIE and IS&T

Topics

Modeling ; Cancer ; Breast

Citation

Rangaraj M. Rangayyan ; Denise Guliato ; Juliano D. de Carvalho and Sérgio A. Santiago
"Polygonal approximation of contours based on the turning angle function", J. Electron. Imaging. 17(2), 023016 (May 22, 2008). ; http://dx.doi.org/10.1117/1.2920413


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.