Faculty Publications

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Publications by NITK Faculty

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Subject: search.filters.subject.Shadow removal

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    Hybrid shadow restitution technique for shadow-free scene reconstruction
    (Springer Verlag service@springer.de, 2014) Muthukumar, M.; Nallaperumal, K.; Subban, R.; Perumalsamy, P.; Shashikala, S.; Selva Kumar, S.; Devi, S.
    Shadows are treated as a noise in computer vision scenario, even though it may found useful in many applications. This research focuses the insignificant shadow restitution methodology to improve the scene visibility and to support the dynamic range reduction. The Hybrid technique combines the physical, geometric, textural, spatial and photometric features for shadow detection. Using feature importance statistics the appropriate criteria is chosen and applied. The experiments over wide dataset prove that the proposed hybrid technique outperforms peer research proposals with the expense of computational cost and time. The output results in a shadow-free, visually plausible high quality image. © Springer International Publishing Switzerland 2014.
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    Automatic shadow removal algorithm for VOP, DWT based watermarking algorithm for VOP and generation of super resolved VOP
    (2011) Pais, A.R.; D'Souza, J.; Reddy, R.M.; Hari Krishna, P.
    Removal of shadow from Video Object Planes (VOPs) will assist in surveillance applications for comprehensive detection of activities. We have proposed a method for removal of shadows from the VOP. Also noise removal is done using existing methods from the VOP. To authenticate the surveillance VOP, digital watermarking is used. We have proposed digital watermarking using localized Biorthogonal wavelets for VOP. Super-resolved VOP is generated using multi-frame method. Edge model based super resolution method is used to get the better results. Also the effect of digital watermarking is studied for the super-resolved VOP. A number of test cases have been proposed and found out a best method for video surveillance application. Our proposed super resolution (SR) method gives better results than bilinear and bi-cubic methods.
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    Super-resolution video generation algorithm for surveillance applications
    (Maney Publishing Suite 1C, Joseph's Well, Hanover Walk Leeds LS3 1AB, 2014) Pais, A.R.; D'Souza, J.; Reddy, R.M.
    Video surveillance is one of the major applications where high-resolution (HR) images are crucial. Since the video camera has limited spatial and temporal resolution, there is a need for super resolution video generation algorithms. In this paper, we have presented a novel technique for activity detection in the surveillance video. To achieve this goal, we have proposed and investigated efficient algorithms for Video Object Plane (VOP) generation, shadow removal from VOP and super-resolved VOP generation, for activity detection from surveillance video. The proposed VOP generation algorithm is computationally efficient and works for both dynamic and static backgrounds. The novel shadow removal algorithm for the VOP is based on texture and its performance has been studied based on average shadow detection and discrimination rates. The proposed super-resolution video generation algorithm has been designed using edge models. The performance of this algorithm has been evaluated using a numerical analysis technique and is found to be better than bi-cubic and bi-linear interpolation techniques. © 2014 RPS.