VLSI Design for Foreground Object Segmentation with Labeling and Noise Reduction Mode in Video Surveillance Application

• Main Authors: De-Zhang Peng, 彭德彰
• Other Authors: Tsung-Han Tsai
• Format: Others
• Language: en_US
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/62771497746572163025

碩士 === 國立中央大學 === 電機工程研究所 === 97 === In computer vision applications, such as video surveillance, human-machine interaction and object based video compression standard (e.g., MPEG-4), most applications attempt to detect, recognize events and tracking foreground objects. There also have many real-time applications. The foreground objects segmentation result will do great influence to later process. Therefore how to reduce a foreground objects segmentation result noise effect is very important. In many video surveillance application need to transform image into a symbolic image to do later post-process (e.g., tracking and recognize). By above-mentioned requisitions, this paper proposed VLSI design for real-time foreground object segmentation with labeling and noise reduction mode. Our proposed VLSI design has high throughput rate that can meet the high resolution specification (e.g., HD720P) with real-time requirement and low cost design. In this paper system consists three parts. First, a foreground objects segmentation architecture design with multi-model background maintenance algorithm is proposed to segment video image. Second, morphological operation noise reduction architecture is proposed to reduce segmentation result noise. Finally, object labeling architecture is proposed to label noiseless image. In this paper proposed systems is implementation by cell-base design flow digital VLSI in TSMC 0.18um.