Turkish fingerspelling recognition system using Generalized Hough Transform, interest regions, and local descriptors

Authors:
Oğuz Altun;Songül Albayrak
Affiliations:
Yildiz Technical University, Computer Engineering Department, 34349 Istanbul, Turkey;Yildiz Technical University, Computer Engineering Department, 34349 Istanbul, Turkey
Venue:
Pattern Recognition Letters
Year:
2011

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Abstract

This paper presents a computer vision system that can recognize Turkish fingerspelling sign hand postures by a method based on the Generalized Hough Transform, interest regions, and local descriptors. A novel method for calculating the reference point for the Generalized Hough Transform, and a simpler but more effective Hough voting strategy are proposed. The stages of implementing a Generalized Hough Transform are examined in detail, and the issues that affect the method success are discussed. The system is tested on a data set with 29 classes of non-rigid hand postures signed by three different signers on non-uniform backgrounds. It attains a 0.93 success rate.