Title: OBJECTS EXTRACTION FOR LICENSE PLATE DETECTION

Year of Publication: 2013
Page Numbers: 431-438
Authors: Charbel Fares
Conference Name: The Third International Conference on Digital Information Processing and Communications (ICDIPC2013)
- United Arab Emirates

Abstract:


In this paper we are presenting an intelligent system to extract objects in an image. We have to specify the shapes that need to be detected as well as its dimensions. Examples are given in the radar application in order to detect license plate in a radar image. A comparative study is done in order to show the most effective contour detection method for this application. The masks used for this comparison are: Sobel, Canny, Prewitt, Roberts, Log and Zerocorss. The study shows that Sobel is the most effective for such type of applications. Then three methods were used for the object extraction. Two known methods were used: Hough Transform and Watershed. The third method is a new Hybrid Segmentation algorithm. Results show that the proposed algorithm is the fastest with a time of execution of 0.8 seconds for images of size 658x486 pixels.