---
title: "Appearance Based Recognition Methodology for Recognising Fingerspelling Alphabets"
authors:
  - "M. G. Suraj"
  - "D. S. Guru"
doi: ""
url: "https://ijcai.org/proceedings/2007/96"
pdf: "https://ijcai.org/proceedings/2007/0096.pdf"
venue: "Proceedings of the Twentieth International Joint Conference on Artificial Intelligence"
year: 2007
pages: "605-609"
track: ""
keywords:
---

# Appearance Based Recognition Methodology for Recognising Fingerspelling Alphabets

M. G. Suraj, D. S. Guru

*Proceedings of the Twentieth International Joint Conference on Artificial Intelligence*, pages 605-609.

## Abstract

In this paper, a study on the suitability of an appearance based model, specifically PCA based model, for the purpose of recognising fingerspel-ling (sign language) alphabets is made. Its recognition performance on a large and varied real time dataset is analysed. In order to enhance the performance of a PCA based model, we suggest to incorporate a sort of pre-processing operation both during training and recognition. An exhaustive experiment conducted on a large number of fingerspelling alphabet images taken from 20 different individuals in real environment has revealed that the suggested pre-processing has a drastic impact in improving the performance of a conventional PCA based model.