DocumentCode :
2134657
Title :
Object detection in X-ray images based on object candidate extraction and support vector machine
Author :
Yan Wang ; Jing Huang
Author_Institution :
Dept. of Basic subjects, China Maritime Police Acad., Ningbo, China
fYear :
2013
fDate :
23-25 July 2013
Firstpage :
173
Lastpage :
177
Abstract :
In this paper, an adaptive region-growing method based on image histogram is used in image segmentation. The seeds are selected according to image histogram distribution. After segmentation, object candidates are obtained by combining the segmented regions according to the proposed rules. Finally, the object detection is completed by using Support Vector Machine. The proposed methods of image segmentation and object candidates extraction are simple and easy to operate, and the candidate extraction needs less requirement of segmentation. The exact shape of the candidate can be gained rather than the rectangle of the object. The experimental results prove that the correct results are obtained by using the proposed methods.
Keywords :
X-ray imaging; feature extraction; image segmentation; object detection; support vector machines; X-ray images; adaptive region-growing method; image histogram distribution; image segmentation; object candidate extraction; object detection; support vector machine; Feature extraction; Histograms; Image segmentation; Lungs; Object detection; Support vector machines; Training; image segmentation; object candidate; object detection; support vector machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2013 Ninth International Conference on
Conference_Location :
Shenyang
Type :
conf
DOI :
10.1109/ICNC.2013.6817965
Filename :
6817965
Link To Document :
بازگشت