Simple and efficient approach for shadow removal from a single-image
In this paper, we present a simple and efficient shadow removal for single natural images. Shadows in image can help and reveal information about illumination sources as well as object’s shape and orientation. However, in computer vision, the presence of shadow will adversely affect the results of some algorithms such as image segmentation, object tracking … Thus, in natural images processing, it is imperative to detect the presence of the shadow and if necessary eliminate it. This work proposes an efficient approach for shadow detection and subsequently elimination in natural images where textural features are used in the detection process while photometric features are used for shadow elimination. We first analyze texture information’s and proximity in terms of similarity between a pair of segmented regions to identify shaded regions. And for removal, we use a Gaussian model to estimate the value of the free-shadow region based on the histogram information. To evaluate the performance of the proposed approach, experimentations are made on several type of shadow.
Disclaimer/Regarding indexing issue:
We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.