An Efficient Image Stitching Method for Heterogeneous Car Videos Based on Bounding Boxes of Features

Chun Ming Tsai, Frank Shih

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Heterogeneous car video recorders can capture scene information with different modalities including viewing angles, resolutions, and lens sensors. Traditional methods cannot accurately perform image stitching on the images captured by heterogeneous cameras. This paper presents an efficient method to stitch heterogeneous images by allowing a driver to view an ultra-wide angle without blind spots. It extracts bounding boxes of brake lights and license plate numbers as feature points to be matched. A homography matrix is computed to stitch the heterogeneous video images. Experimental results show that our proposed method can stitch images accurately and efficiently, which is superior to the existing methods.

Original languageEnglish (US)
Article number1755008
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Volume31
Issue number5
DOIs
StatePublished - May 1 2017

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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