Earticle

초록

영어

This paper presents a real-time pedestrian detection algorithm for a night environment. By first converting the nighttime image data to the L * a * b * color space, it can be extracted in the area L * with robust noise reduction and contrast adjustment. This data is used to generate pre-data through image subtraction. A background image is generated using the data, and the Cascade Histogram of Oriented Gradient &Kalman filter (CH & K) algorithm is proposed to track the movement of pedestrians. In addition, pre-processing algorithms and the proposed algorithm can replace Histograms of Oriented Gradients (HOGs) with rather heavy computations, and sensitive Haar-like features in the night can be used for real-time pedestrian detection and brightness.

목차

Abstract
 1.Introduction
 2. Related Theory
  2.1. Lab Color Space
  2.2. Cascade
  2.3. Hog
 3. Proposed Method
  3.1. Color Space Conversion
 4. Experimental Results
 5. Conclusion
 Acknowledgment
 References

키워드

저자

• Jun-Gyu Park [ Dong-A University, Dept. of Electronics Engineering, 37, Nakdong-daero 550beon-gil, Saha-gu, Busan,Korea ]
• Dae-Seong Kang [ Dong-A University, Dept. of Electronics Engineering, 37, Nakdong-daero 550beon-gil, Saha-gu, Busan,Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605