VEHICLE LICENSE PLATE DETECTION AND RECOGNITION

• TABLE OF CONTENTS ACKNOWLEDGEMENTS ............................................................................................................... II LIST OF FIGURES ...................................................................................................................... V ABSTRACT .................................................................................................................................... VII 

Chapter ONE

INTRODUCTION

• AND BACKGROUND ................................................................... 1  
• 1.1Research Topic and Objectives ................................................................................................. 1  
• 1.2Challenges ......................................................................................................................... 2  
• 1.3Background and Related Work ............................................................................................... 3  1.
• 3.1License Plate Detection ....................................................................................................... 4  1.
• 3.2Character Segmentation ....................................................................................................... 13  1.
• 3.3License Plate Recognition ..................................................................................................... 15 
• 1.4Overview of Our Methods ...................................................................................................... 16 2 LICENSE PLATE DETECTION ................................................................................................ 18 
• 2.1Scanning Window ............................................................................................................... 18  
• 2.2HOG Features .................................................................................................................... 20  2.
• 2.1Feature Extraction Procedure (for Dense-HOG) .............................................................. 21  2.
• 2.2Implementation .............................................................................................................. 24  
• 2.3Support Vector Machine ......................................................................................................... 24 
• 2.4Non-maximum Suppression ..................................................................................................... 26  
• 2.5Refinement of the Algorithm................................................................................................. 29 2.
• 5.1Edge Information.............................................................................................................. 29 2.
• 5.2Scale Adaption..................................................................................................................... 30 
• 2.6Results and Discussion ........................................................................................................... 30 
• 2.7Summary ............................................................................................................................. 31 3 LICENSE PLATE RECOGNITION ............................................................................................ 32  
• 3.1License Plate Alignment Using Color Information................................................................... 34  3.
• 1.1License Plate Alignment Without Angles.............................................................................. 34  3.
• 1.2License Plate Alignment With Angles............................................................................ 38  
• 3.2Plate Binarization Using K-means Clustering........................................................................... 40  3.
• 2.1K-means Clustering.............................................................................................................. 41  
• 3.3Character Segmentation Using an Innovative Histogram-based Model ................................. 43  
• 3.4Digit Characters and Capital Letters Recognition Using Simple Robust Features .................. 48  3.
• 4.1Using Bag-of-words Model: Voting Schemes........................................................................ 49  3.
• 4.2Using SVM Classifier.......................................................................................................... 53  
• 3.5Data set and Results ............................................................................................................ 54  
• 3.6Summary.................................................................................................................................... 57 4 REAL TIME EMBEDDED SYSTEM ............................................................................................ 58  
• 4.1Hardware Part...................................................................................................................... 58  
• 4.2Software Part.........................................................................................................................59  4.
• 2.1The Main Board Side............................................................................................................. 59  4.
• 2.2The Child Board Side........................................................................................................ 60  
• 4.3Implementation..................................................................................................................... 62  4.
• 3.1Kernel Module................................................................................................................... 62  4.
• 3.2Main Board Program.......................................................................................................... 63  4.
• 3.3Socket and TCP................................................................................................................. 63  4.
• 3.4Child Board Program........................................................................................................ 64  
• 4.4Results and Discussion.................................................................................................................................... 64 5 CONCLUSIONS AND FUTURE WORK ................................................................................. 66 REFERENCES .............................................................................................................................. 67