Object-shape classification and reconstruction from tactile images using image gradient

Garima Singh, Anwesha Khasnobish, Arindam Jati, Saugat Bhattacharyya, Amit Konar, D. N. Tibarewala, R. Janarthanan

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

7 Citations (Scopus)

Abstract

A human explores the world around him through his sense to touch. Touch sensation enables us to understand shape, texture and hardness of an object/surface necessary for efficient exploration. Incorporating artificial haptic sensory systems in rehabilitative aids and in various other human computer interfaces enhances the dexterity. This paper presents a novel approach of shape reconstruction and classification from the tactile images by touching the surface of various real life objects. Here four objects (viz. a planar surface, object with one edge, a cuboid i.e. object with two edges and a cylindrical object) have been used for the shape recognition purpose. A new gradient based feature extraction technique has been used for the classification purpose. The reconstruction algorithm also uses image gradients to differentiate between a surface having continuous curvature and a surface having sharp edge. Prewitt masks are used for determining the gradients. A comparison between the performances of different classifiers has been drawn to prove the efficacy of the shape classification algorithm.

Original languageEnglish
Title of host publicationProceedings - 2012 3rd International Conference on Emerging Applications of Information Technology, EAIT 2012
PublisherIEEE
Pages93-96
Number of pages4
ISBN (Print)9781467318259
DOIs
Publication statusPublished - 11 Jan 2013
Event2012 3rd International Conference on Emerging Applications of Information Technology, EAIT 2012 - Kolkata, India
Duration: 30 Nov 20121 Dec 2012

Publication series

NameProceedings - 2012 3rd International Conference on Emerging Applications of Information Technology, EAIT 2012

Conference

Conference2012 3rd International Conference on Emerging Applications of Information Technology, EAIT 2012
CountryIndia
CityKolkata
Period30/11/121/12/12

Keywords

  • Feed Forward Neural Network (FFNN)
  • k-Nearest Neighbor (kNN)
  • Linear Discriminant Analysis (LDA)
  • linear support vector machine (LSVM)
  • reconstruction
  • Shape classification
  • Support Vector Machine with Gaussian Radial Basis Function kernel (SVM-RBF)
  • tactile image

Fingerprint Dive into the research topics of 'Object-shape classification and reconstruction from tactile images using image gradient'. Together they form a unique fingerprint.

Cite this