期刊論文
| 學年 | 102 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2014-02-25 |
| 作品名稱 | A new method of moving object detection using adaptive filter |
| 作品名稱（其他語言） | |
| 著者 | Hsia, Chih-Hsien; Wu, Tsung-Cheng; Chiang, Jen-Shiun |
| 單位 | 中國文化大學電機工程學系研究所 淡江大學電機工程學系 |
| 出版者 | Heidelberg: Springer |
| 著錄名稱、卷期、頁數 | Journal of Real-Time Image Processing 13(2), p.311–325 |
| 摘要 | In many real-world video analysis systems , the available resources are constrained, which limits the image resolution. However, the low computational complexity and fast response for low-resolution images still make them attractive for computer vision applications. This work presents a new model that uses a least-mean-square scheme to train the mask operation for low-resolution images. This efficient and real-time method, which uses an adaptive least-mean-square scheme (ALMSS), uses the training mask to detect moving objects on resource-limited systems. The detection of moving objects is a basic and important task in video surveillance systems, which affects the results of any post-processing, such as object classification, object identification and the description of object behaviors. However, the detection of moving objects in a real environment is a difficult task because of noise issues, such as fake motion or noise. The ALMSS method effectively reduces computational cost for both fake motion environment. The experiments using real scenes indicate that the proposed ALMSS method is effective in the real-time detection of moving objects. This method can be implemented in hardware for high-resolution applications, such as full-HD images. A prototype VLSI circuit is designed and simulated using a TSMC 0.18 μm 1P6M process. |
| 關鍵字 | Image resolution;Least-mean-square (LMS);Adaptive least-mean-square scheme (ALMSS);Detection of moving objects |
| 語言 | en |
| ISSN | 1861-8219 |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | 江正雄 |
| 審稿制度 | 是 |
| 國別 | DEU |
| 公開徵稿 | |
| 出版型式 | ,電子版,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/100930 ) |