Rectangular Shape Detection with an Application to License Plate Detection

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.

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