Vehicle Detection Method using Haar-like Feature on Real Time SystemSungji Han, Youngjoon Han and Hernsoo Hahn

Introduction

•HYPOTHESIS GENERATION• Detecting the distant region using a shadow feature

• Detecting vertical edge using Haar-like feature

• Determining the candidate regions

•HYPOTHESIS VERIFICATION• Verification using complexity of vehicles

• Final verification using vehicle’s symmetric feature

HYPOTHESIS GENERATION

Detecting the distant region using a shadow feature

• Brightness normalization

Detecting the distant region using a shadow feature

• Determining the shadow point in each height.

Detecting vertical edge using Haar-like feature

•Haar-Like Feature

•Better than Sobel and Prewitt

Detecting vertical edge using Haar-like feature

•Compare to Sobel result

Determining the candidate regions

•HYPOTHESIS VERIFICATION

Verification using complexity of vehicles

Final verification using vehicle’s symmetric feature

EXPERIMENTAL RESULT & CONSIDERATION

Detection Methods

Sobel Prewitt Haar

Time(ms) 2 2 3

Result Images

DETECTING RATE

Position Same Lane Side Lane

Dedecting Rate(%)

91.2 76.2

Error Results

Conclusion

• It is proper to apply it to the real-time system.

• It has a limit to detect vehicles using single camera.

Thank You