TY - GEN
T1 - Design and application of novel morphological filter used in vehicle detection
AU - Gochoo, Munkhjargal
AU - Bayanduuren, Damdinsuren
AU - Khuchit, Uyangaa
AU - Battur, Galbadrakh
AU - Tan, Tan Hsu
AU - Kuo, Sy Yen
AU - Huang, Shih Chia
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/23
Y1 - 2016/8/23
N2 - In this paper we represent our proposed novel morphological filter developed under the scope of Taiwan-Mongolian co-project. We applied the implemented filter in vehicle detection from CCTV video signal. Our goalwas to develop a filter that can reduce the noise in background subtracted binary image, which created by camera shake, and unnecessary moving objects such as wave of the tree etc. We compared our filter performance with morphological open, close, erosion, dilation, and median filters. PSNR (Peak Signal to Noise Ratio) is employed for evaluating the performance of the filters, our filter's PSNR was relatively higher (21.39) than the other method. Furthermore, we used our filter for vehicle detection, and detection rate was 100% as the other methods. Thus, we conclude the new filter is sufficient for denoising binary image, and suitable for vehicle detection.
AB - In this paper we represent our proposed novel morphological filter developed under the scope of Taiwan-Mongolian co-project. We applied the implemented filter in vehicle detection from CCTV video signal. Our goalwas to develop a filter that can reduce the noise in background subtracted binary image, which created by camera shake, and unnecessary moving objects such as wave of the tree etc. We compared our filter performance with morphological open, close, erosion, dilation, and median filters. PSNR (Peak Signal to Noise Ratio) is employed for evaluating the performance of the filters, our filter's PSNR was relatively higher (21.39) than the other method. Furthermore, we used our filter for vehicle detection, and detection rate was 100% as the other methods. Thus, we conclude the new filter is sufficient for denoising binary image, and suitable for vehicle detection.
KW - algorithm
KW - digital filter
KW - image processing
KW - new method
KW - vehicle detection
UR - http://www.scopus.com/inward/record.url?scp=84988014909&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84988014909&partnerID=8YFLogxK
U2 - 10.1109/ICIS.2016.7550798
DO - 10.1109/ICIS.2016.7550798
M3 - Conference contribution
AN - SCOPUS:84988014909
T3 - 2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings
BT - 2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings
A2 - Uehara, Kuniaki
A2 - Nakamura, Masahide
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2016
Y2 - 26 June 2016 through 29 June 2016
ER -