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24-11-2017, 11:59 PM

Hello! I am Oana, a student at Umich and I would like to test you shadow detection code for a homework project. Thank you!

jaseela123d · 25-11-2017, 10:40 AM

Obstruction of light by objects creates shadows in a scene. An object can cast a shadow on itself, called its own shadow. The shadow areas are less illuminated than the surrounding areas. In some cases, shadows provide useful information, such as the relative position of an object from the source. But they cause problems in artificial vision applications such as segmentation, object detection and object counting. Therefore, the detection and elimination of shadows is a task of previous processing in many applications of vision by computer. According to the intensity, shadows are of two types, hard and soft shadows. Soft shadows retain the texture of the background surface, while hard shadows are too dark and have little texture. Therefore, the detection of hard shadows is complicated since they can be confused as dark objects instead of shadows. Most of the methods of detection of shadows need multiple images for the calibration of the camera. But the best technique must be able to extract shadows from a single image. It is also difficult to distinguish dark objects and shadows from a single image. This document provides a simple method to detect and remove shadows from a single RGB image. A method for detecting shadows is selected based on the average value of the RGB image in planes A and B of the LAB equivalent of the image. The elimination of the shadow is done by multiplying the shaded region by a constant. Illumination is not uniform in a shaded region. Toward the limit of the shadow, diffusion occurs. Therefore, filtering is done to reduce errors in the shaded limit.

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