Abstract
A novel method for extraction of moving objects in an image sequence using multi-tiered Pulse-Coupled Neural Network (PCNN) is presented in this paper. PCNN is a biologically-inspired model which shows highly applicable in various image processing applications, including image segmentation, contour detection, etc. In order to adapt PCNN for moving object extraction, the multi-tiered PCNN model is proposed. This new PCNN model is called E-PCNN, since excitatory term and external linking are its two features. The architecture and algorithm of E-PCNN are presented in detail. It is shown that E-PCNN outweighs the commonly used inter-frame difference algorithm, having three main advantages: utilization of multiple color information, parameter robustness and robustness against noise.
| Original language | English |
|---|---|
| Pages | 73-78 |
| Number of pages | 6 |
| Publication status | Published - 2004 Dec 1 |
| Externally published | Yes |
| Event | SICE Annual Conference 2004 - Sapporo, Japan Duration: 2004 Aug 4 → 2004 Aug 6 |
Conference
| Conference | SICE Annual Conference 2004 |
|---|---|
| Country/Territory | Japan |
| City | Sapporo |
| Period | 04/8/4 → 04/8/6 |
Keywords
- E-PCNN
- Multi-tiered
- Pulse-Coupled Neural Networks
- Robust motion detection
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering