Loading

Dynamic Features Descriptor for Road User Recognition Using Hierarchal Graph Dynamic Gradient Pattern
Ma’moun Al-Smadi1, Khairi Abdulrahim2, Rosalina Abdul Salama3

1Ma’moun Al-Smadi, Faculty of Science and Technology, Universiti Sains Islam Malaysia (USIM), Negeri Sembilan, Bandar Baru Nilai, Nilai, Malaysia.
2Khairi Abdulrahim, Faculty of Engineering and Built Environment, Universiti Sains Islam Malaysia (USIM), Negeri Sembilan, Bandar Baru Nilai, Nilai, Malaysia.
3Rosalina Abdul Salama, Faculty of Science and Technology, Universiti Sains Islam Malaysia (USIM), Negeri Sembilan, Bandar Baru Nilai, Nilai, Malaysia.
Manuscript received on 25 March 2019 | Revised Manuscript received on 04 April 2019 | Manuscript Published on 27 April 2019 | PP: 414-418 | Volume-7 Issue-6S2 April 2019 | Retrieval Number: F10490476S219/2019©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Accurate and precise vehicle recognition and classification play a major role in analyzing and understanding traffic surveillance systems. This paper proposes a dynamic feature descriptor to recognize and classify road users based on graph representation. Local gradient patterns are computed based on the grayscale difference on the four directions across the center pixels. Dynamic gradients are determined according to the effective gradient computed as the mean value of all gradients. Hierarchal Graph using angular rotation pattern are applied to extract Dynamic Gradient Patterns (DGP). The central pixel is represented by Hierarchal Graph of Dynamic Gradient Patterns (HG-DGP).The proposed method learns dynamic representation adaptively to achieve efficient recognition with higher accuracy and lower pre-processing. The experimental results show that the proposed technique combined with support vector machine is efficient and discriminative for road user recognition and classification.
Keywords: Dynamic Recognition Pattern Hierarchal Graph Support.
Scope of the Article: Pattern Recognition