Pedestrian Segmentation in Infrared Images Based on Local Autocorrelation

被引：0
|
作者：
Wu, Tao [1 ,2 ]
Zeng, Shaogeng [2 ]
Yang, Junjie [1 ,2 ]
机构：
[1] Guangdong Engn & Technol Dev Ctr E learning, 29 Cunjin Rd, Zhanjiang 524048, Peoples R China
[2] Lingnan Normal Univ, Sch Informat Sci & Technol, 29 Cunjin Rd, Zhanjiang 524048, Peoples R China
来源：
EIGHTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2016) | 2016年 / 10033卷
关键词：
Image thresholding; image segmentation; infrared image processing; Moran's I; feature fusion;
D O I：
10.1117/12.2243727
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
In order to select the optimal threshold for pedestrian segmentation in infrared images, a novel algorithm based on local autocorrelation is proposed. The algorithm calculates the local autocorrelation feature of a given image. Next, it constructs a new feature matrix based on this spatial correlation and the original grayscale. Then, it obtains an automatic threshold related with local combined features using the geometrical method based on histogram analysis. Finally, it extracts the image region of pedestrian and yields the binary result. It is indicated by the experiments that, the proposed method performs good result of pedestrian region extraction and thresholding, and it is reasonable and effective.
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页数：6
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