Logo Recognition: Theory and Practice, 1st Edition (Hardback) book cover

Logo Recognition

Theory and Practice, 1st Edition

By Jingying Chen, Lizhe Wang, Dan Chen

CRC Press

192 pages | 79 B/W Illus.

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Description

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.

Reviews

"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

Table of Contents

Introduction

Motivation

Shape recognition

Proposed method

Objectives

Assumptions and input data

Book organization

Preliminary knowledge

Statistics

Probability

Random variable

Expected value

Variance and deviation

Covariance and correlation

Moment-generating function

Fourier transform

Structural and syntactic pattern recognition

Introduction

Grammar-based passing method

Graph-based matching methods

Neural network

Architecture

Learning process

Summary

Review of shape recognition techniques

2D shape recognition

Shape representation

Shape recognition approaches

Logo recognition

Statistical approach

Syntactic/structural approach

Neural network

Hybrid approach

Polygonal approximation

Indexing

Matching

Distance measure

Hausdorff distance

Summary

System overview

Preprocessing

Polygonal approximation

Indexing

Matching

Polygonal approximation

Feature point detection overview

Dynamic two-strip algorithm

The proposed method

Results

Comparison with other methods

Summary

Logo indexing

Normalization

Indexing

Reference angle indexing (filter 1)

Line orientation indexing (filters 2 and 3)

Experimental results

Summary

Logo matching

Hausdorff distance

Modified LHD (MLHD)

Experimental results

Matching results

Degradation analysis

Results analysis with respect to the LHD and the MHD

Discussion and comparison with other methods

Summary

Applications

Mobile visual search with GetFugu

Using logo recognition for anti-phishing and Internet brand monitoring

The LogoTrace library

Real-time vehicle logo recognition

Summary

Conclusion

Book summary

Contribution

Future work

Book conclusion

References

Appendix Test images

Appendix Results of feature point detection

Index

Subject Categories

BISAC Subject Codes/Headings:
COM021030
COMPUTERS / Database Management / Data Mining
COM037000
COMPUTERS / Machine Theory
TEC015000
TECHNOLOGY & ENGINEERING / Imaging Systems