Publication Type:

Conference Paper


2017 International Conference on Communication and Signal Processing (ICCSP), IEEE, Chennai, India (2017)



chromaticity image, color invariant method, Computer vision, computer vision algorithms, entropy, entropy minimization, illumination invariant image, illumination invariant shadow free image, Image color analysis, image colour analysis, Image edge detection, image log chromaticity, image shadow removal, Lighting, shadow free chromaticity image, shadow removal, Two dimensional displays, Visualization


Shadows are caused when light from a source of light is blocked by opaque objects. In the field of image processing, the shadow cause many technical difficulties. Shadows may give us a wrong interpretation of the shape, colour, or orientation of the image. Objects may appear to merge, when shadow of one object falls on another object and making the object count lesser. Hence removal of shadows is a very crucial and inevitable task of many of computer vision algorithms, such as segmentation, object detection and tracking etc. Shadows are caused due to illumination variation. An object may have a shadow in a particular illumination but the same object would not have a shadow in a different illumination. This paper deals with removal of shadows using illumination invariant methods based on the fact that an illumination invariant image is a shadow free image. The resultant illumination invariant shadow free image can be used as the input to those applications, where the presence of shadow causes adverse effect. The first step of the method is to find the log chromaticity of image. Next step is to obtain the 1D invariant image. Shadow free chromaticity image is then obtained from the illumination invariant image for better display of the output image. The proposed method is implemented and the results obtained proved the superiority of the method.

Cite this Research Publication

A. Krishnan, Jayadevan, P., and Vinitha Panicker J, “Shadow removal from single image using color invariant method”, in 2017 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 2017.