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Automated Color Logo Recognition Technique using Color and Hog Features

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Upasana Maity, Joydeep Mukherjee
10.5120/ijca2017914715

Upasana Maity and Joydeep Mukherjee. Automated Color Logo Recognition Technique using Color and Hog Features. International Journal of Computer Applications 170(2):38-41, July 2017. BibTeX

@article{10.5120/ijca2017914715,
	author = {Upasana Maity and Joydeep Mukherjee},
	title = {Automated Color Logo Recognition Technique using Color and Hog Features},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2017},
	volume = {170},
	number = {2},
	month = {Jul},
	year = {2017},
	issn = {0975-8887},
	pages = {38-41},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume170/number2/28046-2017914715},
	doi = {10.5120/ijca2017914715},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

This research work purposes an automated system for the identification of the color logo images. Color logo images are recognized using a color feature namely Color Moments and an Histogram Oriented Gradients feature. Color is modeled using Mean and Standard Deviation. Firstly we extract color moments feature from an image, and then we consider histogram analysis and make a summation of each color color bin. Classification is done using Support Vector Machine Classifier (SVM). Experimental verification is done using a dataset of 500 images divided into 10 classes.

References

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Keywords

Logo recognition, color features, histogram features, SVM classifier.