Paper Info
Title
Enhancement Of Accuracy Of Hand Shape Recognition Using Color Calibration By Clustering Scheme And Majority Voting Method
Abstract
This paper presents methods of enhancing the recognition accuracy of hand shapes in a scheme which is proposed by the authors as being easy to memorize and which can represent much information. To ensure suitability for practical use, the recognition performance must be maintained even when there are changes in the illumination environment. First, a color calibration process using a k-means clustering scheme is introduced as a way of ensuring high performance in color detection. In the proposed method the thresholds for hue values are decided before the recognition process, as a color calibration scheme. The second method of enhancing accuracy involves making a majority decision. Many image frames are obtained from one hand shape before the transition to the next shape. The frames in this hand shape formation time span are used for shape recognition by majority voting based on the recognition results from each frame. It has been verified by carrying out experiments under different illumination conditions that the proposed technique can raise the recognition performance.
Year
DOI
Venue
2014
10.1007/978-3-319-07731-4_26
HUMAN INTERFACE AND THE MANAGEMENT OF INFORMATION: INFORMATION AND KNOWLEDGE DESIGN AND EVALUATION, PT I
Keywords
Field
DocType
Color Gloves, Shape Recognition, Color Detection, Hue Value, Clustering, Majority Voting, Illumination Environment
Computer vision,Shape formation,Color detection,Pattern recognition,Color calibration,Computer science,Hue,Artificial intelligence,Cluster analysis,Majority rule
Conference
Volume
ISSN
Citations 
8521
0302-9743
2
PageRank 
References 
Authors
0.53
3
3
Name
Order
Citations
PageRank
Takahiro Sugaya161.43
Hiromitsu Nishimura2477.82
Hiroshi Tanaka35613.71