Vehicle make and model recognition using random forest classification for intelligent transportation systems

Muhammad Asif Manzoor; Yasser Morgan

doi:10.1109/CCWC.2018.8301714

Vehicle make and model recognition using random forest classification for intelligent transportation systems

Muhammad Asif Manzoor, Yasser Morgan

Department of Systems and Enterprises

University of Regina

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

17 Scopus citations

Abstract

Intelligent Transportation System (ITS) has many real world applications. ITS applications help in better traffic management and enable us to make more secure, intelligent, smart decisions regarding traffic networks. Automatic Surveillance and monitoring is required for many ITS applications. Vehicle Make and Model Recognition (VMMR) can be used to recognize the vehicles' identity. We have designed a Random Forest based VMMR system in this work to identify the Make and Model of a vehicle. The proposed VMMR system is evaluated using a publicly available dataset. Scale Invariant Feature Transform (SIFT) and Histogram of Oriented Gradients (HOG) are used for the representation of vehicle images. The proposed method identifies the vehicles with good recognition rates and results are discussed in this paper.

Original language	English
Title of host publication	2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018
Editors	Satyajit Chakrabarti, Himadri Nath Saha
Pages	148-154
Number of pages	7
ISBN (Electronic)	9781538646496
DOIs	https://doi.org/10.1109/CCWC.2018.8301714
State	Published - 22 Feb 2018
Event	8th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2018 - Las Vegas, United States Duration: 8 Jan 2018 → 10 Jan 2018

Publication series

Name	2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018
Volume	2018-January

Conference

Conference	8th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2018
Country/Territory	United States
City	Las Vegas
Period	8/01/18 → 10/01/18

Keywords

Bag of Features (BoF) Model
Histogram of Oriented Gradient (HOG)
Make and Model Recognition
Random Forest
Scale Invariant Feature Transform (SIFT)
Vehicle Classification

Access to Document

10.1109/CCWC.2018.8301714

Cite this

Manzoor, M. A., & Morgan, Y. (2018). Vehicle make and model recognition using random forest classification for intelligent transportation systems. In S. Chakrabarti, & H. N. Saha (Eds.), 2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018 (pp. 148-154). (2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018; Vol. 2018-January). https://doi.org/10.1109/CCWC.2018.8301714

Manzoor, Muhammad Asif ; Morgan, Yasser. / Vehicle make and model recognition using random forest classification for intelligent transportation systems. 2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018. editor / Satyajit Chakrabarti ; Himadri Nath Saha. 2018. pp. 148-154 (2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018).

@inproceedings{d476f13b2e0d4420a7b1219121e5fbcd,

title = "Vehicle make and model recognition using random forest classification for intelligent transportation systems",

abstract = "Intelligent Transportation System (ITS) has many real world applications. ITS applications help in better traffic management and enable us to make more secure, intelligent, smart decisions regarding traffic networks. Automatic Surveillance and monitoring is required for many ITS applications. Vehicle Make and Model Recognition (VMMR) can be used to recognize the vehicles' identity. We have designed a Random Forest based VMMR system in this work to identify the Make and Model of a vehicle. The proposed VMMR system is evaluated using a publicly available dataset. Scale Invariant Feature Transform (SIFT) and Histogram of Oriented Gradients (HOG) are used for the representation of vehicle images. The proposed method identifies the vehicles with good recognition rates and results are discussed in this paper.",

keywords = "Bag of Features (BoF) Model, Histogram of Oriented Gradient (HOG), Make and Model Recognition, Random Forest, Scale Invariant Feature Transform (SIFT), Vehicle Classification",

author = "Manzoor, {Muhammad Asif} and Yasser Morgan",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 8th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2018 ; Conference date: 08-01-2018 Through 10-01-2018",

year = "2018",

month = feb,

day = "22",

doi = "10.1109/CCWC.2018.8301714",

language = "English",

series = "2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018",

pages = "148--154",

editor = "Satyajit Chakrabarti and Saha, {Himadri Nath}",

booktitle = "2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018",

}

Manzoor, MA & Morgan, Y 2018, Vehicle make and model recognition using random forest classification for intelligent transportation systems. in S Chakrabarti & HN Saha (eds), 2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018. 2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018, vol. 2018-January, pp. 148-154, 8th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2018, Las Vegas, United States, 8/01/18. https://doi.org/10.1109/CCWC.2018.8301714

Vehicle make and model recognition using random forest classification for intelligent transportation systems. / Manzoor, Muhammad Asif; Morgan, Yasser.
2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018. ed. / Satyajit Chakrabarti; Himadri Nath Saha. 2018. p. 148-154 (2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Vehicle make and model recognition using random forest classification for intelligent transportation systems

AU - Manzoor, Muhammad Asif

AU - Morgan, Yasser

PY - 2018/2/22

Y1 - 2018/2/22

N2 - Intelligent Transportation System (ITS) has many real world applications. ITS applications help in better traffic management and enable us to make more secure, intelligent, smart decisions regarding traffic networks. Automatic Surveillance and monitoring is required for many ITS applications. Vehicle Make and Model Recognition (VMMR) can be used to recognize the vehicles' identity. We have designed a Random Forest based VMMR system in this work to identify the Make and Model of a vehicle. The proposed VMMR system is evaluated using a publicly available dataset. Scale Invariant Feature Transform (SIFT) and Histogram of Oriented Gradients (HOG) are used for the representation of vehicle images. The proposed method identifies the vehicles with good recognition rates and results are discussed in this paper.

AB - Intelligent Transportation System (ITS) has many real world applications. ITS applications help in better traffic management and enable us to make more secure, intelligent, smart decisions regarding traffic networks. Automatic Surveillance and monitoring is required for many ITS applications. Vehicle Make and Model Recognition (VMMR) can be used to recognize the vehicles' identity. We have designed a Random Forest based VMMR system in this work to identify the Make and Model of a vehicle. The proposed VMMR system is evaluated using a publicly available dataset. Scale Invariant Feature Transform (SIFT) and Histogram of Oriented Gradients (HOG) are used for the representation of vehicle images. The proposed method identifies the vehicles with good recognition rates and results are discussed in this paper.

KW - Bag of Features (BoF) Model

KW - Histogram of Oriented Gradient (HOG)

KW - Make and Model Recognition

KW - Random Forest

KW - Scale Invariant Feature Transform (SIFT)

KW - Vehicle Classification

UR - http://www.scopus.com/inward/record.url?scp=85047418375&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85047418375&partnerID=8YFLogxK

U2 - 10.1109/CCWC.2018.8301714

DO - 10.1109/CCWC.2018.8301714

M3 - Conference contribution

AN - SCOPUS:85047418375

T3 - 2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018

SP - 148

EP - 154

BT - 2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018

A2 - Chakrabarti, Satyajit

A2 - Saha, Himadri Nath

T2 - 8th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2018

Y2 - 8 January 2018 through 10 January 2018

ER -

Manzoor MA, Morgan Y. Vehicle make and model recognition using random forest classification for intelligent transportation systems. In Chakrabarti S, Saha HN, editors, 2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018. 2018. p. 148-154. (2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018). doi: 10.1109/CCWC.2018.8301714

Vehicle make and model recognition using random forest classification for intelligent transportation systems

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this