Colour logo and trademark detection in unconstrained images using colour edge gradient co-occurrence histograms

In this paper, we present an extension of the Colour Edge Co-occurence Histogram (CECH) object detection scheme for detecting logos and trademarks in unconstrained colour images. We introduce more accurate information to the CECH by virtue of incorporating colour edge detection using vector order st...

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Bibliographic Details
Main Authors: Phan, R., Chia, J., Androutsos, D.
Format: Conference Proceeding
Language:English
Subjects:
colour edge detection
Colour Edge Gradient Co-occurrence Histogram (CEGCH)
Content based retrieval
Histograms
HSV quantization
Image edge detection
Image retrieval
Object detection
pattern recognition
Pixel
Quantization
Solids
Statistics
Trademarks
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Summary:In this paper, we present an extension of the Colour Edge Co-occurence Histogram (CECH) object detection scheme for detecting logos and trademarks in unconstrained colour images. We introduce more accurate information to the CECH by virtue of incorporating colour edge detection using vector order statistics, producing a more accurate representation of edges in images, as compared to the simple colour difference edge classification which is done in the CECH. Our proposed method is thus reliant on edge gradient information, and so we call it the Colour Edge Gradient Co-occurrence Histogram (CEGCH). We also illustrate a colour quantization scheme based in the Hue-Saturation-Value (HSV) colour space, illustrating that it is more suitable for logo and trademark detection in comparison to the colour quantization scheme used with the CECH. Results illustrate that the CEGCH detects logos and trademarks with greater accuracy in comparison to the CECH.
ISSN:0840-7789
2576-7046
DOI:10.1109/CCECE.2008.4564591