Abstract
Shadow detection is of broad interest in computer vision. In this article, a new shadow detection method for single color images in outdoor scenes is proposed. Shadows attenuate pixel intensity, and the degrees of attenuation are different in the three RGB color channels. Previously, we proposed the Tricolor Attenuation Model (TAM) that describes the attenuation relationship between shadows and their non-shadow backgrounds in the three color channels. TAM can provide strong information on shadow detection; however, our previous study needs a rough segmentation as the pre-processing step and requires four thresholds. These shortcomings can be overcome by adding intensity information. This article addresses the problem of how to combine TAM and intensity and meanwhile to obtain a threshold for shadow segmentation. Simple and complicated shadow images are used to test the proposed method. The experimental results and comparisons validate its effectiveness.
Highlights
Shadow detection is highly desirable for a wide range of applications in computer vision, pattern recognition, and image processing
The attached shadow is the part of an object that is not illuminated by direct light; the cast shadow is the dark area projected by an object on the background
Tricolor Attenuation Model (TAM) describes the attenuation relationship between shadows and their non-shadow backgrounds in the three color channels, and this relationship can be used for shadow detection
Summary
Shadow detection is highly desirable for a wide range of applications in computer vision, pattern recognition, and image processing. TAM describes the attenuation relationship between shadows and their non-shadow backgrounds in the three color channels, and this relationship can be used for shadow detection. Based on the TAM image, the multistep shadow detection algorithm is previously proposed [1]. 2. using the mean value over each sub-region to binarizate the TAM images and to obtain initial shadows.
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