Earticle

초록

영어

According to the traffic light recognition problem of intelligent vehicle, this paper proposes a traffic light recognition algorithm based on compressive tracking. First, the candidate regions of traffic light are extracted. Second, after extracting the HOG feature of candidate regions, using the machine learning for classification and recognition, compressive tracking algorithm is used to track lights that have been identified a automatically. This algorithm combines feature recognition and tracking identification of traffic light and traffic light changes in scale and color can be identified normally. The algorithm proposed in this paper has been tested on actual road in intelligent vehicle; traffic light recognition effect is good.

목차

Abstract
 1. Introduction
 2. Identification Based on Features
  2.1. Color Segmentation
  2.2. Morphological Operations
  2.3. Shape Segmentation
  2.4. Feature Extraction
  2.5. Classifier Training and Recognition
 3. Recognition Based On Compression Tracking
  3.1. Compressive Sensing Principle
  3.2. Compressive Tracking
  3.3. Identification
 4. Results and Discussion
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Xuanru Zhou [ Beijing Key Laboratory of Information Service Engineering, Beijing Union University ]
• Jiazheng Yuan [ Beijing Key Laboratory of Information Service Engineering, Beijing Union University ]
• Hongzhe Liu [ Beijing Key Laboratory of Information Service Engineering, Beijing Union University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605