Abstract
Problem statement: The shape-based logo recognition systems have been developed to automate the logo registration process. The logo recognition operation faces many challenges such as having to recognize logos that might be scaled, rotated, translated and added with noises. Different types of logo’s shapes further add to the complex nature of this problem. Approach: We developed a logo recognition system that comprises of three phases: Preprocessing, feature extraction and features matching. For feature extraction, we adopted a region-based Angular Radial Transform (ART) to extract the features from logo’s shapes. We used the Euclidian Distance (ED) as a similarity measure parameter for the features matching. Results: We tested the system that used the ART as feature extraction method on a large logo database of 2730 images to investigate the effect of several deformations and noise on recognition performance. The experimental results showed the system that use the ART features was robust against the size changing, had an excellent discrimination power against different types of noises and good immunity to rotations. The performance evaluation results showed that ART technique perform better than Zernike moments and Invariant moment’s techniques. Conclusion: The proposed ART descriptor was very effective to describe all types of logo’s shapes independent on different types of deformations and noise. It also represented the logo’s shapes in concise manner without information redundancy.
Highlights
In the logo recognition system the adopted shape increasing of the provided products and services, the description method has the most important effect on the logos are specially designed to serve as identification to recognition performance
The Invariant moments are usually used to describe the simplest type of logos that is the device marks and that is interpret the insufficient in the description performance to cope the other complex types of logos, on the other hand the authors in (Amayeh et al, 2003) have been reported that the Zernike Moments (ZM) descriptor is variant under translation and scaling
A new shape-based logo recognition system using Angular Radial Transform descriptor (ART) has been proposed. It has been tested on developed large logo database of 2730 logo images
Summary
Logo provides a powerful visual clue to image identity (Hwang and Kim, 2006). In the logo recognition system the adopted shape increasing of the provided products and services, the description method has the most important effect on the logos are specially designed to serve as identification to recognition performance. A logo represents the goodwill of the descriptor have invariant properties against different business, particular manufacturer or producer and used types of deformations such as scaling, noise, translation to prevent the consumer from becoming confused or and rotation. It is should have enough description misled about the origins or sources. The logo of power to the different complex shapes of logos: Wordeach brand should be unique To handle this aim, the in-mark (logo that contains only characters or words in logo registration office perform infringement test to the mark), Device-mark (contains graphical or ensure that the new logo symbol is not identical to each figurative elements only), Composed-mark The radial basis function is defined by a cosine function: Am (θ)
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