Object shape recognition from tactile images using regional descriptors

Garima Singh, Arindam Jati, Anwesha Khasnobish, Saugat Bhattacharyya, Amit Konar, D. N. Tibarewala, Atulya K. Nagar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

This paper presents a novel approach of shape recognition from the tactile images by touching the surface of various real life objects. Here four geometric shaped objects (viz. a planar surface, object with one edge, a cubical object i.e. object with two edges and a cylindrical object) are used for shape recognition. The high pressure regions denoting surface edges have been segmented out via multilevel thresholding. These high pressure regions hereby obtained were unique to different object classes. Some regional descriptors have been used to uniquely describe the high pressure regions. These regional descriptors have been employed as the features needed for the classification purpose. Linear Support Vector Machine (LSVM) classifier is used for object shape classification. In noise free environment the classifier gives an average accuracy of 92.6%. Some statistical tests have been performed to prove the efficacy of the classification process. The classifier performance is also tested in noisy environment with different signal-to-noise (SNR) ratios.

Original languageEnglish
Title of host publicationProceedings of the 2012 4th World Congress on Nature and Biologically Inspired Computing, NaBIC 2012
PublisherIEEE
Pages53-58
Number of pages6
ISBN (Print)9781467347686
DOIs
Publication statusPublished - 7 Jan 2013
Event2012 4th World Congress on Nature and Biologically Inspired Computing, NaBIC 2012 - Mexico City, Mexico
Duration: 5 Nov 20129 Nov 2012

Publication series

NameProceedings of the 2012 4th World Congress on Nature and Biologically Inspired Computing, NaBIC 2012

Conference

Conference2012 4th World Congress on Nature and Biologically Inspired Computing, NaBIC 2012
CountryMexico
CityMexico City
Period5/11/129/11/12

Keywords

  • Feed Forward Neural Network (FFNN)
  • k-Nearest Neighbor (kNN)
  • Linear Discriminant Analysis (LDA)
  • Linear Support Vector Machine (LSVM)
  • Shape Recognition
  • tactile image

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  • Cite this

    Singh, G., Jati, A., Khasnobish, A., Bhattacharyya, S., Konar, A., Tibarewala, D. N., & Nagar, A. K. (2013). Object shape recognition from tactile images using regional descriptors. In Proceedings of the 2012 4th World Congress on Nature and Biologically Inspired Computing, NaBIC 2012 (pp. 53-58). [6402239] (Proceedings of the 2012 4th World Congress on Nature and Biologically Inspired Computing, NaBIC 2012). IEEE. https://doi.org/10.1109/NaBIC.2012.6402239