Comparison of Techniques for Vehicle Plate Location Detection for a Multi-Camera Tracking System
スポンサーリンク
概要
- 論文の詳細を見る
The aim of this study is to construct a multi-camera tracking system for vehicle plate recognition. Generally, recognizing a vehicle plate for a toll-gate system or parking system is easier than recognizing a car plate in a highway system. There are many cameras installed on the highway to capture images and every camera has different angles of images. As a result, the images are captured in varied imaging conditions and not focusing on the vehicle plate itself. Therefore, we need a system that is able to recognize the location of a vehicle plate first. In this paper we will propose different techniques for vehicle plate location detection. First, we used segmentation method and second we applied Fast Fourier Transform and histogram method to recognize the location of a vehicle plate. The result will be discussed and the methods are compared at the end of this paper.
- 2006-10-28
著者
-
Musa Zalili
Graduate School Of Information Production And Systems Waseda University
-
Watada Junzo
Graduate School Of Information Production And Systems Waseda University
関連論文
- Dynamic Tracking System Using Foot Step Direction(Contribution to 21 Century Intelligent Technologies and Bioinformatics)
- Comparison of Techniques for Vehicle Plate Location Detection for a Multi-Camera Tracking System
- FUND ALLOCATION METHOD BASED ON A BLOCK OF SHARES
- FUZZY AR MODEL OF STOCK PRICE
- A Biologically Inspired Computing Approach to Solve Cluster-Based Determination of Logistic Problem(Contribution to 21 Century Intelligent Technologies and Bioinformatics)
- Analysis of Logistics Based on DNA Computing
- Applied Statistics by Means of DNA-Based Clustering for Data Classification
- Risk Assessment of a Portfolio Selection Model Based on a Fuzzy Statistical Test
- Building a Bio-Inspired Reinforcement Medical Network System for Optimal Relationships in Medical Communications(INNOVATIVE BIOMEDICAL TECHNOLOGIES and INFORMATICS, BMFSA2008)
- Portfolio Selection Models with Technical Analysis-Based Fuzzy Birandom Variables
- Solving Bilevel Programming Problems Using a Neural Network Approach and Its Application to Power System Environment