An Implementation of Floral Scent Recognition System Using ICA Combined with Correlation Coefficients

Authors:
Byeong-Geun Cheon;Yong-Wan Roh;Dong-Ju Kim;Kwang-Seok Hong
Affiliations:
School of Information and Communication Engineering, Sungkyunkwan University, Suwon, South Korea 440-746;School of Information and Communication Engineering, Sungkyunkwan University, Suwon, South Korea 440-746;School of Information and Communication Engineering, Sungkyunkwan University, Suwon, South Korea 440-746;School of Information and Communication Engineering, Sungkyunkwan University, Suwon, South Korea 440-746
Venue:
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Year:
2009

Citing 1
Cited 1

Face recognition by independent component analysis

IEEE Transactions on Neural Networks

A method of multiple odors detection and recognition

HCII'11 Proceedings of the 14th international conference on Human-computer interaction: interaction techniques and environments - Volume Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

We propose a floral scent recognition system using ICA combined with correlation coefficients estimated by statistical analysis between floral scent and prescribed reference models. The proposed floral scent recognition system consists of three modules such as floral scent acquisition module using Metal Oxide Semiconductor (MOS) sensor array, entropy-based floral scent detection module, and floral scent recognition module using ICA combined with correlation coefficients. To evaluate the proposed floral scent recognition system, we implemented an individual floral scent recognition system using K-NN with PCA that are generally used in conventional electronic noses. In the experimental results, the proposed system achieves higher performance than traditional odor recognition methods. We confirmed that the proposed system is practical and effective.