Title :
Rectangular Shape Detection with an Application to License Plate Detection
Author :
Qi Li ; Yongyi Gong
Author_Institution :
Dept. of Comput. Sci., Western Kentucky Univ., Bowling Green, KY, USA
Abstract :
Rectangular shape detection has a wide range of applications, such as license plate detection, vehicle detection and building detection. In this paper, we propose a robust framework for rectangular shape detection based on the channel-scale space of RGB images. The framework consists of algorithms developed to address two issues of a shape attention (i.e., a connected component of edge points), including: i) openness and ii) fragmentation. Furthermore, we propose an interestness measure for rectangular shapes by integrating interest points Our case study on license plate detection shows the promise of the proposed framework.
Keywords :
image colour analysis; object detection; shape recognition; RGB images; algorithms; building detection; channel-scale space; fragmentation; license plate detection; rectangular shape detection; robust framework; shape attention; Context; Educational institutions; Image edge detection; Image segmentation; Licenses; Shape; Transforms;
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2013 IEEE 25th International Conference on
Conference_Location :
Herndon, VA
Print_ISBN :
978-1-4799-2971-9
DOI :
10.1109/ICTAI.2013.55