0

Full Content is available to subscribers

Subscribe/Learn More  >
Proceedings Article

Gradient feature matching for in-plane rotation invariant face sketch recognition

[+] Author Affiliations
Ann Theja Alex, Vijayan K. Asari, Alex Mathew

The Univ. of Dayton (United States)

Proc. SPIE 8661, Image Processing: Machine Vision Applications VI, 866107 (March 6, 2013); doi:10.1117/12.2005750
Text Size: A A A
From Conference Volume 8661

  • Image Processing: Machine Vision Applications VI
  • Philip R. Bingham; Edmund Y. Lam
  • Burlingame, California, USA | February 03, 2013

abstract

Automatic recognition of face sketches is a challenging and interesting problem. An artist drawn sketch is compared against a mugshot database to identify criminals. It is a very cumbersome task to manually compare images. This necessitates a pattern recognition system to perform the comparisons. Existing methods fall into two main categories - those that allow recognition across modalities and methods that require a sketch/photo symthesis step and then copare in some modality. The methods that require synthesis require a lot of computing power since it involves high time and space complexity. Our method allows recognition across modalities. It uses the edge feature of a face sketch and face photo image to create a feature string called 'edge-string' which is a polar coordinate representation of the edge image. To generate a polar coordinate representation, we need the reference point and reference line. Using the center point of the edge image as the reference point and using a horizontal line as the reference line is the simplest solution. But, it cannot handle in-plane rotations. For this reason, we propose an approach for finding the reference line and the centroid point. The edge-strings of the face photo and face sketch are then compared using the Smith-Waterman algorithm for local string alignments. The face photo that gave the highest similarity score is the photo that matches the test face sketch input. The results on CUHK (Chinese University of Hong Kong) student dataset show the effectiveness of the proposed approach in face sketch recognition. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Ann Theja Alex ; Vijayan K. Asari and Alex Mathew
" Gradient feature matching for in-plane rotation invariant face sketch recognition ", Proc. SPIE 8661, Image Processing: Machine Vision Applications VI, 866107 (March 6, 2013); doi:10.1117/12.2005750; http://dx.doi.org/10.1117/12.2005750


Access This Article
Sign In to Access Full Content
Please Wait... Processing your request... Please Wait.
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
 

Figures

Tables

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

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

Advertisement

Buy this article ($18 for members, $25 for non-members).
Sign In