Employing Mobile Applications in Human-Machine Interaction in Visual Pattern Recognition Research

  • Amir SchurEmail author
  • Charles C. Tappert
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 528)


This study is part of the first author’s continued dissertation research in human-machine interaction in visual pattern recognition. Previous research focused on evaluating human-machine interaction using a flower recognition tool. Initial research showed that human interaction in color recognition improved accuracy significantly. We then looked more deeply into various automated color recognition algorithms and ways of combining them with human feedback. Described here is the process of upgrading the initial system into a new mobile application using Appinventor. After data collection, models were built for various color spaces. Sharing this experience may help other researchers incorporating a human-computer interaction component into their work.


Human-computer interaction Visual object recognition Pattern classification Feature extraction Appinventor Color space 


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    Schur, A., Tappert, C.: Combining human and machine capabilities for improved accuracy and speed in visual recognition tasks. In: Stephanidis, C. (ed.) HCI 2014, Part I. CCIS, vol. 434, pp. 368–372. Springer, Heidelberg (2014)CrossRefGoogle Scholar
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    Ugarriza, L.G., et al.: Automatic image segmentation by dynamic region growth and multiresolution merging. IEEE Trans. Image Process. 18(10), 2275–2288 (2009)CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Seidenberg School of CSISPace UniversityWhite PlainsUSA

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