Latest Issue
Service Restoration in the Distribution System with Voltage Control Devices using Improved Sequential Opening Branches (ISOB)
Published: December 31,2024Physico-chemical Characteristics of Rice-based Cereal Processed by Twin-screw Extrusion and Microwave Cooking
Published: December 31,2024Investigation of the Influence of Extrusion Conditions on Cambodian Extruded Rice Vermicelli
Published: December 31,2024Application of High-Pressure and High-Temperature Reactor for Extraction of Essential Oil from Kaffir Lime Peel
Published: December 31,2024Optimal Placement of Electric Vehicle Charging Stations Using Mixed-Integer Linear Programming: A Case Study in Cambodia
Published: December 31,2024Minimum Standard of Traffic Safety Devices at Primary School Zone Black Spot in Phnom Penh
Published: December 31,2024Displacement-Based Formulation with Non-Penetration Constraint for Planar Composite Beams in Partial Interaction Using the Coupled Connector Model
Published: December 31,2024Effect of Different Water-Saving Irrigation Methods for Rice Cultivation, Case Study in Cambodia.
Published: December 31,2024Should water taxi service in Phnom Penh be abandoned or sustained?
Published: December 31,2024THE 13TH SCIENTIFIC DAY (Catalyzing Innovation : Human Capital, Research, and Industry Linkages)
Published: August 23,2024Cambodian Vehicle License Plate Localization
-
1. Department of Electrical and Energy Enginpeering
Institute of Technology of Cambodia, Russian Ferderation Blvd., P.O. Box 86, Phnom Penh, Cambodia.
Academic Editor:
Received: January 20,2024 / Revised: Accepted: January 20,2024 / Published: June 01,2013
Localization of the plate region is one of the critical tasks in the automatic vehicle license plate recognition (AVLPR) system. In this work, the algorithm for Cambodian license plate localization based on the mid-gray image removal combined with the connected component analysis (CCA) is proposed. We test our proposed technique with 70 images which are captured from some distances and viewpoints. As the result of the simulation, it shows the success rate of 98.57% for overall images in our image dataset.