Used by companies, organizations, and even individuals to promote recognition of their brand, logos can also act as a valuable means of identifying the source of a document. E-business applications can retrieve and catalog products according to their logos. Governmental agencies can easily inspect goods using smart mobile devices that use logo recognition techniques. However, because logos are two-dimensional shapes of varying complexity, the recognition process can be challenging. Although promising results have been found for clean logos, they have not been as robust for noisy logos.
Logo Recognition: Theory and Practice is the first book to focus on logo recognition, especially under noisy conditions. Beginning with an introduction to fundamental concepts and methods in pattern and shape recognition, it surveys advances in logo recognition. The authors also propose a new logo recognition system that can be used under adverse conditions such as broken lines, added noise, and occlusion.
The proposed system introduces a novel polygonal approximation, a robust indexing scheme, and a new line segment Hausdorff distance (LHD) matching method that can handle more distortion and transformation types than previous techniques. In the first stage, raw logos are transformed into normalized line segment maps. In the second stage, effective line pattern features are used to index the database to generate a moderate number of likely models. In the third stage, an improved LHD measure screens and generates the best matches. A comprehensive overview of logo recognition, the book also presents successful applications of the technology and suggests directions for future research.
"I was inspired by this book project at the very beginning; now the book appears to be even a better idea when I really have it in hand. The resulting appraisal is thoughtful, creative, and comprehensive."
—From the Foreword by Professor Xiaoli Li, College of Information Science and Technology, Beijing Normal University
"… Overall the book is well written and easy to follow … understandable and well formulated. I recommend it to readers willing to learn about logo recognition systems and potential commercial applications of shape recognition tools."
—Journal of Intelligent and Robotic Systems
Assumptions and input data
Variance and deviation
Covariance and correlation
Structural and syntactic pattern recognition
Grammar-based passing method
Graph-based matching methods
Review of shape recognition techniques
2D shape recognition
Shape recognition approaches
Feature point detection overview
Dynamic two-strip algorithm
The proposed method
Comparison with other methods
Reference angle indexing (filter 1)
Line orientation indexing (filters 2 and 3)
Modified LHD (MLHD)
Results analysis with respect to the LHD and the MHD
Discussion and comparison with other methods
Mobile visual search with GetFugu
Using logo recognition for anti-phishing and Internet brand monitoring
The LogoTrace library
Real-time vehicle logo recognition
Appendix Test images
Appendix Results of feature point detection