Description

Rain detection and removal using OpenCV

Abstract

         The detection of bad weather conditions is crucial for meteorological centers, specially with demand for air, sea and ground traffic management. In this project, a system based on computer vision is presented which detects the presence of rain or snow. To separate the foreground from the background in image sequences, a classical Gaussian Mixture Model is used. The foreground model serves to detect rain and snow, since these are dynamic weather phenomena. Selection rules based on photometry and size are proposed in order to select the potential rain streaks. Then a Histogram of Orientations of rain or snow Streaks (HOS), estimated with the method of geometric moments, is computed, which is assumed to follow a model of Gaussian-uniform mixture. 

Proposed system

      When the presence of rain or of snow is detected, the HOS makes it possible to detect the pixels of rain or of snow in the foreground images, and to estimate the intensity of the precipitation of rain or of snow.    

Applications

• detection of critical weather conditions
• the observation of weather, the reliability improvement of video-surveillance systems
• rain rendering.