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JACIII Vol.23 No.1 pp. 97-101
doi: 10.20965/jaciii.2019.p0097
(2019)

Short Paper:

The Framework of Passable Region Recognition Based on Vanish-Line

Xintian Cheng

Jinling Institute of Technology
Room 522, No.99, Hongjing Road, Nanjing, Jiangsu, China

Received:
April 26, 2018
Accepted:
June 18, 2018
Published:
January 20, 2019
Keywords:
unstructured, normalized cross correlation, weight-accuracy
Abstract

For the defect of the traditional vanishing point detection algorithm that is invalid in unstructured environment, a novel vanishing detection algorithm based on Dynamic Template Matching (DTM) is proposed. And a framework of access area recognition is put forward according to the vanishing point line. First, a series of lines are selected from the image in the form of the scanning at the same interval and then calculate the between each line and the previous one. The horizontal position of vanish point is that of the line with the minimum normalized correlation value in all scanning line. Second, a new image is constructed by getting rid of the part above of the viewpoint line, and be divided into several subimages without overlap to extract the multi features. The end, a train set is constructed based on the assumption of no deviation of the vehicle and the test set is classified by multi-kernel learning (MKL) method to obtain passable area. In addition, according to the need of intelligent vehicles during working, a weight-accuracy is delimited by assigning the different weights to the near areas and far areas. This kind of accuracy is more significative than the original one. In the experiments on various environments image sets, the proposed method exhibits favorable performances compared to the other methods.

Cite this article as:
X. Cheng, “The Framework of Passable Region Recognition Based on Vanish-Line,” J. Adv. Comput. Intell. Intell. Inform., Vol.23, No.1, pp. 97-101, 2019.
Data files:
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Last updated on Feb. 20, 2019