雙計數器背景註冊法應用於移動物體偵測

Two-Counter Method on Background Registration for Moving Object Segmentation

陳信名(Hsin-Ming Chen)

指導教授 ： 陳永耀

國立臺灣大學/電機資訊學院/電機工程學研究所/碩士(2005年)

https://doi.org/10.6342/NTU.2005.01290

摘要

智慧型監測系統應用於許多場合，也是個有趣的研究主題，經由智慧型的判斷，可以降低許多人力成本以及人為疏失。
本論文提出以雙計數器為基礎之移動物體分割演算法,並希望應用於居家看護系統。此方法作為人體動作判別的前端處理。在移動物體分割部份，首先利用差異值統計圖去自動取得門檻值以適應於不同的拍攝環境，有效地將移動的物體從畫面中分離出來，並利用形態學的運算子去補償切割後的畫面和消除陰影的影響，最後，本論文利用統計的概念去更新背景的資訊，提出一個雙計數器背景註冊法，建立具有可靠性的背景，使系統能夠有效的應用在各種不同的監測環境之下。

關鍵字

門檻值決定 ； 背景註冊 ； 智慧型監測系統

並列摘要

In this thesis, we designed a two-counter background registration method on moving object segmentation which is an important front-end process for human activity recognition.
In moving object segmentation, we can use histograms of different values to determine the threshold value for automatic noise elimination in different picture frames. Moving objects are separated from the background in the current frame effectively with the proposed threshold method. The morphological operator is then used to eliminate the background noise of the segmentation results and shadows of the moving objects. Finally, we use the statistic conception to update the background information. We propose the Two-Counter background registration algorithm to reconstruct the reliable background information effectively for different surveillance environments.

並列關鍵字

threshold determines ； background registration ； Intelligent surveillance system

參考文獻

[1] I. Koprinska, S. Carrato, ``Temporal video segmentation: a survey,' Signal Processing: Image Communication, vol. 16, pp. 477--500, 2001.

[2] F. Ziliani, A. Cavallaro, “Image Analysis for Video Surveillance Based on Spatial Regularization of a Statistical Model-Based Change Detection” Real-Time Imaging, vol. 7, no. 5, pp. 389-399(11), Oct. 2001.

[3] J.M. Gauch, ” Image segmentation and analysis via multiscale gradient watershed hierarchies”, IEEE Transactions on Image Processing, Vol. 8, Issue 1, pp. 69 – 79, Jan. 1999.

[4] I. Vanhamel, I. Pratikakis, H. Sahli, ” Multiscale gradient watersheds of color images”, IEEE Transactions on Image Processing, Vol. 12, Issue 6, pp. 617 – 626, June 2003.

[5] Munchurl Kim, Jae Gark Choi, Daehee Kim, Hyung Lee, Myoung Ho Lee, Chieteuk Ahn, Yo-Sung Ho, ”A VOP generation tool: automatic segmentation of moving objects in image sequences based on spatio-temporal information”, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 9, Issue 8, pp. 1216 – 1226, Dec. 1999.