Characterization of the reception environment of GNSS signals using a texture and color based adaptive segmentation technique

This paper is focused on the characterization of GNSS signals reception environment by estimating the percentage of visible sky. A new segmentation technique based on a color watershed using an adaptive combination of color and texture information is proposed. This information is represented by two morphological gradients, a classical color gradient and a texture gradient based on co-occurrence matrices. The segmented images are then used as input for a k-means classifier in order to determine the percentage of visible sky in fish-eye images. The obtained classification results are evaluated to demonstrate the effectiveness and the reliability of the proposed approach.