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Authors: Rina Tagami ; Hiroki Kobayashi ; Shuichi Akizuki and Manabu Hashimoto

Affiliation: Graduate School of Engineering, Chukyo University, Nagoya, Japan

Keyword(s): Template Matching, Pixel Selection, Hue Value, Genetic Algorithm, Object Detection.

Abstract: We propose a fast and reliable method for object detection using color and intensity information. The probability of hue and pixel values (gray level intensity values) in two-pixel pairs occurring in a template image is calculated, and only those pixel pairs with extremely low probability are carefully selected for matching. Since these pixels are highly distinctive, reliable matching is not affected by surrounding disturbances, and since only a very small number of pixels is used, the matching speed is high. Moreover, the use of the two measures enables reliable matching regardless of an object’s color. In a real image experiment, we achieved a recognition rate of 98% and a processing time of 80 msec using only 5% (684 pixels) of the template image. When only 0.5% (68 pixels) of the template image was used, the recognition rate was 80% and the processing time was 5.9 msec.

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Paper citation in several formats:
Tagami, R.; Kobayashi, H.; Akizuki, S. and Hashimoto, M. (2023). Fast and Reliable Template Matching Based on Effective Pixel Selection Using Color and Intensity Information. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP; ISBN 978-989-758-634-7; ISSN 2184-4321, SciTePress, pages 607-614. DOI: 10.5220/0011683600003417

@conference{visapp23,
author={Rina Tagami. and Hiroki Kobayashi. and Shuichi Akizuki. and Manabu Hashimoto.},
title={Fast and Reliable Template Matching Based on Effective Pixel Selection Using Color and Intensity Information},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP},
year={2023},
pages={607-614},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011683600003417},
isbn={978-989-758-634-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP
TI - Fast and Reliable Template Matching Based on Effective Pixel Selection Using Color and Intensity Information
SN - 978-989-758-634-7
IS - 2184-4321
AU - Tagami, R.
AU - Kobayashi, H.
AU - Akizuki, S.
AU - Hashimoto, M.
PY - 2023
SP - 607
EP - 614
DO - 10.5220/0011683600003417
PB - SciTePress

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