Evaluation of Colour Recognition Algorithms with a Palette Designed for Applications which Aid People with Visual Impairment

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Author(s)

Bartosz Papis 1,*

1. Transition Technologies S.A.

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2014.12.01

Received: 24 Jul. 2014 / Revised: 30 Aug. 2014 / Accepted: 7 Oct. 2014 / Published: 8 Nov. 2014

Index Terms

Color, computer vision, machine learning

Abstract

This paper presents the evaluation of three machine learning algorithms applied to colour recognition. The “primary” colour palette is defined in accordance with the results from social sciences. Decision Trees, Support Vector Machines and k-Nearest Neighbours classifiers are being tested on various data sets created for this purpose. One of the distance measures for the k-Nearest Neighbour classifier considered is DeltaE2000 - the standard colour difference formula, designed in conformance with human perception. Additionally, we compare these algorithms to various colour recognition applications available.

Cite This Paper

Bartosz Papis,"Evaluation of Colour Recognition Algorithms with a Palette Designed for Applications which Aid People with Visual Impairment", IJIGSP, vol.6, no.12, pp.1-7, 2014. DOI: 10.5815/ijigsp.2014.12.01

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