Pattern Recognition, ( ISI ), Volume (65), Year (2017-4) , Pages (164-174)

Title : ( Automatic Mineral Identification Using Color Tracking )

Authors: Saeed Aligholi , Gholam Reza Lashkaripour , Reza Khajavi , Morteza Razmara ,

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Abstract

Optical properties of crystals are one of the most powerful features for mineral identification. In this study, a novel automated color-based mineral identification (MI) procedure is developed, which can efficiently incorporate color variations under plane-polarized (PPL) and cross-polarized (XPL) illumination modes. Any unknown mineral is registered by two 19-point sets (under PPL and XPL) in the CIELab color space and the proposed scheme tracks mineral color variations in the CIELab color space. If the corresponding PPL and XPL modified Hausdorff distances (with those of the known mineral) are within acceptable ranges, it can be recognized as a specific mineral. The method is easy to implement compared to methods that examine different color-based features. In addition, not much color information is lost as is the case with feature-based MI schemes. The proposed method, therefore, provides a significant improvement in discriminatory power and compared to conventional methods, the procedure enables reliable and consistent identification over a larger range of minerals.

Keywords

Automated mineral identification; CIELab color space; Modified Hausdorff distance;CIEDE2000 color distance
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@article{paperid:1061524,
author = {Aligholi, Saeed and Lashkaripour, Gholam Reza and Khajavi, Reza and Razmara, Morteza},
title = {Automatic Mineral Identification Using Color Tracking},
journal = {Pattern Recognition},
year = {2017},
volume = {65},
month = {April},
issn = {0031-3203},
pages = {164--174},
numpages = {10},
keywords = {Automated mineral identification; CIELab color space; Modified Hausdorff distance;CIEDE2000 color distance},
}

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%0 Journal Article
%T Automatic Mineral Identification Using Color Tracking
%A Aligholi, Saeed
%A Lashkaripour, Gholam Reza
%A Khajavi, Reza
%A Razmara, Morteza
%J Pattern Recognition
%@ 0031-3203
%D 2017

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