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International Conference on Computing and Information Technology

IC2IT 2019: Recent Advances in Information and Communication Technology 2019 pp 180–190Cite as

The Combination of Different Cell Sizes of HOG with KELM for Vehicle Detection

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 936))

Abstract

HOG has been developed successfully in many intelligent vehicle detection systems. HOG still has interesting problems that consist of (i) redundant features and (ii) ambiguous features (similarities between vehicles and non-vehicles), which problems have an effect on time computation and misclassification. The vertical direction of HOG method (V-HOG) and adding the position of orientation bins and intensity features (πHOG) improve the problems of HOG; but they produce redundant and ambiguous features in various regions of vehicles. This paper proposes a new method for improving the performance of HOG that has flexibility in various regions of vehicles. The proposed method used combines different sized cells of HOG that is called CDC-HOG. The CDC-HOG were conducted on a GTI dataset, which consists of four regions (far, front, left, and right regions). The CDC-HOG is compared with HOG, V-HOG, πHOG, and PHOG; uses the kernel extreme learning machine (KELM), and supports vector machine (SVM) for evaluating features. The CDC-HOG with KELM produced the highest performance in terms of accuracy, true positive rate, and false positive rate for all regions.

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Author information

Authors and Affiliations

  1. Computer Science, Faculty of Informatics, Mahasarakham University, Talat, Thailand

    Natthariya Laopracha

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  1. Natthariya Laopracha
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Correspondence to Natthariya Laopracha .

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Editors and Affiliations

  1. Faculty of Information Technology, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand

    Pongsarun Boonyopakorn

  2. Faculty of Information Technology, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand

    Phayung Meesad

  3. Faculty of Information Technology, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand

    Sunantha Sodsee

  4. LG Kommunikationsnetze, FernUniversität in Hagen, Hagen, Germany

    Herwig Unger

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Laopracha, N. (2020). The Combination of Different Cell Sizes of HOG with KELM for Vehicle Detection. In: Boonyopakorn, P., Meesad, P., Sodsee, S., Unger, H. (eds) Recent Advances in Information and Communication Technology 2019. IC2IT 2019. Advances in Intelligent Systems and Computing, vol 936. Springer, Cham. https://doi.org/10.1007/978-3-030-19861-9_18

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