Unsupervised wide field-of-view video image change detection

Rui Liu; Zhenhong Jia; Xiaohui Huang; Jiajia Wang; Gang Zhou; Fei Shi

doi:10.1117/12.3035276

19 July 2024 Unsupervised wide field-of-view video image change detection

Rui Liu, Zhenhong Jia, Xiaohui Huang, Jiajia Wang, Gang Zhou, Fei Shi

Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 132130G (2024) https://doi.org/10.1117/12.3035276
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China

Abstract

Video surveillance requires simultaneous monitoring of multiple areas. Consequently, real-time automatic change detection of the monitored areas becomes very important. In the context of wide field-of-view conditions, the combination of a wide field-of-view, intricate environmental factors, and a substantial presence of random noise can lead to the degradation of visual fidelity and a diminished signal-to-noise ratio in the video images acquired through the image sensor. As a consequence, the task of detecting subtle changes becomes challenging for the surveillance system. To address the above problems, we have proposed a change detection method that leverages improved difference images and super fast and robust fuzzy c-means with constraints clustering. Initially, we employ an improved log-ratio operator and an improved mean-ratio operator to generate two distinct difference images. Subsequently, the wavelet fusion algorithm is applied to merge these two difference images, effectively integrating their distinctive features and producing a fused difference image with differentiability. Then, the new difference image is subjected to soft threshold primary classification and a cumulative distribution function normalization to obtain the difference image after primary classification. Finally, the super fast and robust fuzzy c-means with constraints clustering algorithm is employed for the ultimate classification, enabling the separation of changed and unchanged areas within the image.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Rui Liu, Zhenhong Jia, Xiaohui Huang, Jiajia Wang, Gang Zhou, and Fei Shi "Unsupervised wide field-of-view video image change detection", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 132130G (19 July 2024); https://doi.org/10.1117/12.3035276

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KEYWORDS

Tunable filters

Image fusion

Video surveillance

Video

Digital filtering

Fuzzy logic

Image filtering

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