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Paper Information

Journal:   JOURNAL OF ARTIFICIAL INTELLIGENCE IN ELECTRICAL ENGINEERING   MAY 2013 , Volume 2 , Number 5; Page(s) 39 To 45.
 
Paper: 

VEHICLE LOGO RECOGNITION USING IMAGE MATCHING AND TEXTURAL FEATURES

 
 
Author(s):  REZAEI NEGIN S., FARAJZADEH NACER*
 
* DEPARTMENT OF INFORMATION TECHNOLOGY, AZARBAIJAN SHAHID MADINI UNIVERSITY, TABRIZ, IRAN
 
Abstract: 

In recent years, automatic recognition of vehicle logos has become one of the important issues in modern cities. This is due to the unlimited increase of cars and transportation systems that make it impossible to be fully managed and monitored by human. In this research, an automatic real-time logo recognition system for moving cars is introduced based on histogram manipulation. In the proposed system, after locating the area that contains the logo, image matching technique and textural features are utilized separately for vehicle logo recognition. Experimental results show that these two methods are able to recognize four types of logo (Peugeot, Renault, Samand and Mazda) with an acceptable performance, 96% and 90% on average for image matching and textural features extraction methods, respectively.

 
Keyword(s): VEHICLE LOGO RECOGNITION, TEXTURAL FEATURES, IMAGE MATCHING, VEHICLE POSITIONING
 
 
References: 
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Click to Cite.
APA: Copy

REZAEI NEGIN, S., & FARAJZADEH, N. (2013). VEHICLE LOGO RECOGNITION USING IMAGE MATCHING AND TEXTURAL FEATURES. JOURNAL OF ARTIFICIAL INTELLIGENCE IN ELECTRICAL ENGINEERING, 2(5), 39-45. https://www.sid.ir/en/journal/ViewPaper.aspx?id=408377



Vancouver: Copy

REZAEI NEGIN S., FARAJZADEH NACER. VEHICLE LOGO RECOGNITION USING IMAGE MATCHING AND TEXTURAL FEATURES. JOURNAL OF ARTIFICIAL INTELLIGENCE IN ELECTRICAL ENGINEERING. 2013 [cited 2021May15];2(5):39-45. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=408377



IEEE: Copy

REZAEI NEGIN, S., FARAJZADEH, N., 2013. VEHICLE LOGO RECOGNITION USING IMAGE MATCHING AND TEXTURAL FEATURES. JOURNAL OF ARTIFICIAL INTELLIGENCE IN ELECTRICAL ENGINEERING, [online] 2(5), pp.39-45. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=408377.



 
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