ABSTRACT
Aiming at the problems of traditional watershed edge detection algorithm in the study of abnormal behavior images of rail transit crowd, such as susceptibility to noise and over-segmentation phenomenon, an image edge detection method based on marked watershed algorithm is proposed. The method first uses a mathematical morphology method for smoothing and edge enhancement, and then uses an improved watershed algorithm based on marker for edge detection to obtain the closed edge of the target image, so as to mark the edge of the target image. The experiments show that compared with the traditional watershed edge detection algorithm, this method can reduce the influence of noise, effectively suppress the over-segmentation phenomenon, improve the edge detection effect, and detect clear and uniform edges, which provides a new image edge detection technique and method for the study of abnormal behavior images of rail transit crowds.
- He Wenhui, Sun Keyang, Wang Bing, Research on Urban Rail Transit Timetable Optimization Considering Air-Rail Transportation. Journal of Railway Science and Engineering, 2022, 19(02):351-358.Google Scholar
- He Yuqiang, Mao Baohua, Song Lili. Research on Passenger Safety Assurance System in Railway Stations under Large-scale Passenger Flow. China Safety Science Journal, 2005, (09): 17-20.Google Scholar
- Yang Guozhu. Current situation analysis and optimization strategy of emergency disposal of high-speed railway. Railway Transport and Economy, 2022, 44(07): 90-95.Google Scholar
- Yang Jingfeng, Zhu Dapeng. Research on Dynamic Distribution Model of Passenger Flow in Railway System under Accidents. Railway Transport and Economy, 2021, 43(06): 21-27.Google Scholar
- Zhu Li. Study on Emergency Treatment of Urban Rail Transit in the Emergent Passenger Flow. Auto Time, 2022, (15): 187-189.Google Scholar
- Dong Xuejuan. Research on Application Scheme of Video Big Data for High-speed Railway Infrastructure. Railway Computer Application, 2022, 31(04): 26-35.Google Scholar
- Jiang Zhengxu. Construction of Intelligent Monitoring System for Rail Transit. China Public Security, 2018, (Z1): 133-136.Google Scholar
- Yang Yimin, Xiao Bin. Research on Safety Assurance System for Heavy Haul Railway Operation. China Safety Science Journal, 2021, 31(S1): 176-180.Google Scholar
- Yu Jinyu, Du Shan, Zhen Tao. Application of Intelligent Video Analysis Technology in Smart Station. Metallurgical Industry Automation, 2022, 46(S1): 194-197.Google Scholar
- Liu Jinming, Zhu Chengbo, Zhou Changyi. Application of Video Face Recognition Technology in Railway Personnel Control. China Railway, 2019, (04): 99-103.Google Scholar
- Rima Chaker, Zaher Al Aghbari and ImranN. Junejo. Social network model for crowd anomaly detection and localization. Pattern Recognition, 2017, 61: 266-281.Google ScholarDigital Library
- WAN Shaohua, XU Xiaolong, WANG Tian, An Intelligent Video Analysis Method for Abnormal Event Detection in Intelligent Transportation Systems. IEEE Transactions on Intelligent Transportation Systems, 2021, 22(7): 4487-4495.Google ScholarDigital Library
- Q Chen, R Wu, Y Ni, Research on human abnormal behavior detection and recognition in intelligent video surveillance. Journal of Computational Information Systems, 2013, 9(1): 289-296.Google Scholar
- Yang Gui, Cai Qizhong, Yang Min, Research on Intelligent Video Monitoring System for Railway Based on DSP. Modern Computer, 2017, (23): 80-84.Google Scholar
- Zhang Yubin, Chen Feng, Lejuan, Methods of detecting and correcting the center of circular mark points in helicopter blade images. Journal of Applied Sciences, 2022, 40(02): 212-223.Google Scholar
- Luan Kuifeng, Liu Shuai, Pan Yujia, High-resolution remote sensing imagery based on improved marker watershed extraction of coastline. Journal of Marine Sciences, 2021, 39(01): 20-28.Google Scholar
- Mao Xinguang. Research on Watershed Image Segmentation Algorithms. Computer Era, 2021, (06): 57-60.Google Scholar
Index Terms
- An Image Edge Detection Method Based on Marked Watershed Algorithm
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