Detection of Roadway Sign Condition Changes using Multi-Scale Sign Image Matching (M-SIM)

作者：Tsai Yichang^*; Hu Zhaozheng; Alberti Chris

来源：Photogrammetric Engineering and Remote Sensing, 2010, 76(4): 391-405.

Roadway signs are important for safety, and transportation agencies need to identify sign condition changes to perform timely maintenance, including replacement. Currently, sign condition changes are inspected manually in the field, which is time consuming, costly, and sometimes dangerous. This paper first proposes a novel algorithm to detect three condition changes: missing, tilted, and blocked signs, using GPS data and video log images. The algorithm consists of three steps: (a) Multi-Scale Sign Image Matching (M-SIM), (b) Image feature analysis, and (c) Sign condition change detection and classification. The algorithm was tested using images with simulated sign condition changes and actual video images taken in Fiscal Year (FY) 2003 and 2005 by the Louisiana Department of Transportation and Development (LADOTD). The tests demonstrate the algorithm is effective to detect three types of sign condition changes. Out of 34,000 actual video log images, the algorithm detected and classified 100 percent of the missing signs, 72.7 percent of the tilted signs, and 66.7 percent of the blocked signs, for an overall 74.3 percent detection rate. These results show that the algorithm is useful for developing an intelligent roadway sign condition change detection system.

• 出版日期2010-4