A rapid texture-based moving object detection method

This paper presents a moving object detection method based on texture information extracted from images. Every image captured from the camera is converted into Local Binary Pattern (LBP). Salient feature points extracted from previous LBP are compared with those features found from the current LBP w...

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Bibliographic Details
Published in2011 8th Asian Control Conference (ASCC) pp. 1205 - 1209
Main Authors Yea-Shuan Huang, Zhi-Hong Ou, Hsiang-Wen Hsieh, Hung-Hsiu Yu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2011
Subjects
Block matching
clustering
Computer vision
Feature extraction
feature point detection
Image motion analysis
motion vector
Object detection
object segmentation
Optical imaging
Pixel
Tracking
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Summary:This paper presents a moving object detection method based on texture information extracted from images. Every image captured from the camera is converted into Local Binary Pattern (LBP). Salient feature points extracted from previous LBP are compared with those features found from the current LBP with a block matching approach so that the corresponding feature points from the successive image frames can be identified. If multiple correspondences exist between feature points, the motion vectors of each feature points are then calculated to determine the best corresponding features on the current LBP. Finally, with clustering of motion vectors, all the moving objects on image frames can be successfully detected and identified. Experimental results show that the average matching accuracy rate is 95.12%, and the average processing time for moving object detection is 46.2ms.
ISBN:9781612844879
1612844871