IEEE Transactions on Pattern Analysis and Machine Intelligence
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
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In this paper, we propose a method to detect and recognize multiple odors, and implement a multiple odor recognition system. Multiple odor recognition technology has not yet been developed, since existing odor recognition techniques which have been researched and developed by components analysis and pattern recognition techniques only deal with single odors at a time. Multiple odors represent a dynamic odor change from no odor to a single odor and multiple odors, which is the most common situation in a real-world environment. Therefore, it is necessary to sense and recognize techniques for dynamic odor changes. To recognize multiple odors, the proposed method must include odor data acquisition using a smell sensor array, odor detection using entropy, feature extraction using Principal Component Analysis, recognition candidate selection using Tree Search, and recognition using Euclidean Distance. To verify the validity of this study, a performance evaluation was conducted using a 132 odor database. As a result, the odor detection rate is approximately 95.83% and the odor recognition rate is approximately 88.97%.