Chalk Print? Feasibility of predicting the lecturer based on his/her chalk leftovers

Authors

Irene Crisologo National Institute of Physics, University of the Philippines Diliman
Jeric Tugaff National Institute of Physics, University of the Philippines Diliman
Anthony Longjas National Institute of Physics, University of the Philippines Diliman
Rene Batac National Institute of Physics, University of the Philippines Diliman
Christopher Monterola National Institute of Physics, University of the Philippines Diliman

Abstract

Penmanship has a high degree of uniqueness as exemplified by the seemingly universal use of hand signature as identifier in contracts validations and property ownerships. In this work, we demonstrate that the distinctiveness of one’s writing patterns is possibly embedded in the molding of chalk tips. Using conventional photometric stereo method, the three-dimensional surface features of chalk tips used in Math and Physics lectures are microscopically resolved. Principal component analysis and neural networks are then combined in identifying the chalk user based on the extracted topography. Results show 50.05% classification accuracy for 10 different individuals, that is four-fold higher than the 12.4% chance proportion criterion from the 369 chalk samples we have collected.

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Issue

2008: Proceedings of the 26th Samahang Pisika ng Pilipinas Physics Congress

Article ID

SPP-2008-PB-35

Section

Poster Session B (Instrumentation, Environmental, and Theoretical Physics)

Published

2008-10-22

How to Cite

[1]

I Crisologo, J Tugaff, A Longjas, R Batac, and C Monterola, Chalk Print? Feasibility of predicting the lecturer based on his/her chalk leftovers, Proceedings of the Samahang Pisika ng Pilipinas 26, SPP-2008-PB-35 (2008). URL: https://proceedings.spp-online.org/article/view/SPP-2008-PB-35.