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19 May 2016 Alpha trimmed correlation for touchless finger image mosaicing
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In this paper, a novel technique to mosaic multiview contactless finger images is presented. This technique makes use of different correlation methods, such as, the Alpha-trimmed correlation, Pearson’s correlation [1], Kendall’s correlation [2], and Spearman’s correlation [2], to combine multiple views of the finger. The key contributions of the algorithm are: 1) stitches images more accurately, 2) provides better image fusion effects, 3) has better visual effect on the overall image, and 4) is more reliable. The extensive computer simulations show that the proposed method produces better or comparable stitched images than several state-of-the-art methods, such as those presented by Feng Liu [3], K Choi [4], H Choi [5], and G Parziale [6]. In addition, we also compare various correlation techniques with the correlation method mentioned in [3] and analyze the output. In the future, this method can be extended to obtain a 3D model of the finger using multiple views of the finger, and help in generating scenic panoramic images and underwater 360-degree panoramas.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shishir P. Rao, Rahul Rajendran, Sos S. Agaian, and Marzena Mary Ann Mulawka "Alpha trimmed correlation for touchless finger image mosaicing", Proc. SPIE 9869, Mobile Multimedia/Image Processing, Security, and Applications 2016, 98690U (19 May 2016);


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