Cross-Perception Fusion Model of Electronic Nose and Electronic Tongue for Black Tea Classification

  • Mahuya Bhattacharyya Banerjee
  • Runu Banerjee Roy
  • Bipan Tudu
  • Rajib Bandyopadhyay
  • Nabarun Bhattacharyya
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 775)


Cross-perception is a perceptual phenomenon that demonstrates an interaction between two or more different sensory perception where the stimulus of one sensory system guides the instinctive response of another sense. In this work, a cross-perception model imitating multiple human’s perception by multi-sensor data fusion was proposed for the instrumental study. “Electronic nose” and “electronic tongue” were employed for detection of aroma and taste respectively of black tea samples. The data collected from two different sensory systems were pre-processed with suitable pre-processing technique and merged prior to further use. Two cross-perception variables i.e. cross correlation factor of aroma on taste and vice versa were assigned using principal component analysis and multiple linear regression. KNN classifier was comparatively used for classification of the conventional fusion model as well as cross-perception multi sensor fusion model. Results indicated that the cross-perception multi-sensors data fusion demonstrated noticeable superiority to the conventional fusion methodologies.


Cross perception E-Nose E-Tongue Data-preprocessing MLR KNN 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • Mahuya Bhattacharyya Banerjee
    • 1
  • Runu Banerjee Roy
    • 1
  • Bipan Tudu
    • 1
  • Rajib Bandyopadhyay
    • 1
    • 3
  • Nabarun Bhattacharyya
    • 2
    • 3
  1. 1.Department of Instrumentation and Electronics EngineeringJadavpur UniversityKolkataIndia
  2. 2.Centre for Development of Advanced ComputingKolkataIndia
  3. 3.Laboratory of Artificial Sensory SystemsITMO UniversitySaint PetersaburgRussia

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