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Volume & Issue no: Volume 3, Issue 6, November - December 2014

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Title:
Feature Analysis using Spiking Neurons with Improved PCA appoach for Hand Gesture Recognition
Author Name:
Nisha Kumari, Roopali Garg, Inderdeep Aulakh
Abstract:
Abstract Gesture recognition allows a computing device to mathematically present human motion. Recognizing gestures makes communication more natural and providing them as an input makes computers more accessible for the physically-impaired. Our work focuses on hand gesture recognition. The presented work is about to recognize the hand gesture by using the concept of spiking neuron approach and PCA approach. The presented work is divided in two main stages. In first stage, the hand gesture image analysis is performed and the feature set is generated. To generate this feature set, spiking neuron approach is applied over the image. This approach is based on the segmented centroid oriented analysis approach so that effective detection of the ROI area and intensity over the area will be identified. This obtained feature set is represented in the form of a neuron curve. The spiking neurons are used for feature extraction. At second stage, the spiking neuron curve for the training dataset and testing input image is classified using PCA approach. Based on this classification process, the prediction value of input image is identified. Now the match of this predicted value is performed with input image. The hand gesture image having the maximum match is considered as the result image. Keywords: Hand Gesture Recognition, Spiking Neurons, Region of Interest, Feature Extraction, Boundary Identification, Principal Component Analysis
Cite this article:
Nisha Kumari, Roopali Garg, Inderdeep Aulakh , " Feature Analysis using Spiking Neurons with Improved PCA appoach for Hand Gesture Recognition" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) , Volume 3, Issue 6, November - December 2014 , pp. 147-150 , ISSN 2278-6856.
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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
ISSN 2278-6856
Frequency : 6 Issues/Year


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