Alpha trimmed correlation for touchless finger image mosaicing

• NCJ Number: 308369
• Author(s): Shishir P. Rao; Rahul Rajendran; Sos S. Agaian; Marzena Mary Ann Mulawka
• Date Published: 2016
• Grant Number(s): 2014-IJ-CX-K003
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical)

Annotation

This paper presents a new method for touchless finger image mosaicing.

Abstract

In this paper, a novel technique to mosaic multiview contactless finger images is presented; computer simulations show that this method produces better or comparable stitched images than several state-of-the-art methods. 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. In addition, the authors 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. (Published Abstract Provided)