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|Other Titles: ||A study on moving objects detection and tracking using symmetric wavelet transform scheme|
|Authors: ||黃丁威;Huang, Ding-wei|
|Keywords: ||監視器系統;對稱遮罩小波轉換架構;偽移動量;移動物件偵測與追蹤;Visual surveillance system;Symmetric Mask-Based Scheme;Fake motion;Moving object detection and tracking|
|Issue Date: ||2010-01-11 07:02:20 (UTC+8)|
In recent years, visual surveillance systems for the purpose of security have been rapidly developed. More and more people try to develop intelligent visual surveillance systems to replace the traditional passive video surveillance systems. The intelligent visual surveillance system can detect moving objects in the initial stage and subsequently process the functions such as object classification, object tracking, and object behaviors description. Detecting moving object is a basic and significant task in every surveillance application. The accurate location of the moving object does not only provide a focus of attention for post-processing but also can reduce the redundant computation for the incorrect motion of the moving object. The successful moving object detection in a real surrounding environment is a difficult task, since there are many kinds of problems such as illumination changes, fake motion, and Gaussian noise in the background that may lead to detect incorrect motion of the moving object.
There are three typical approaches for motion detection: background subtraction, frame difference, and optical flow. Generally, the above three moving object detection methods are all sensitive to illumination changes, noises, and fake motion such as moving leaves of trees. In past years, several approaches for object detecting and tracking for pre-processing were proposed, such as the discrete wavelet transform(DWT) and the low resolution image generated by replacing each pixel value of the original image with the average value of its neighbors and itself. But the LL band image produced by the original image size via two dimensions (row and column) calculation on the conventional DWT may cause high computing cost. These low resolution images become fuzzier than the LL band image generated by using DWT. It may reduce the preciseness of post-processing (such as object tracking and object identification).
To overcome the above-mentioned problems, we propose a method, symmetric mask-based scheme (SMBS), for detecting and tracking moving objects by using symmetric mask-based discrete wavelet transform (SMDWT). In the SMBS, only the LL (5×5) mask band of SMDWT is used. Unlike the traditional DWT method to process row and column dimensions separately by low-pass filter and down sampling, the LL mask band of SMDWT is used to directly calculate the LL band image. Our proposed method can reduce the image transfer computing cost and remove fake motion that is not belonged to the real moving object. Furthermore, we can retain a better slow motion of the object than that of the low resolution method and provide effective and complete moving object regions.
|Appears in Collections:||[電機工程學系暨研究所] 學位論文|
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