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JACIII Vol.17 No.5 pp. 739-745
doi: 10.20965/jaciii.2013.p0739
(2013)

Paper:

Fingernail Detection System Using Differences of the Distribution of the Nail-Color Pixels

Noriaki Fujishima* and Kiyoshi Hoshino**

*Graduate school of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba-shi, Ibaraki 305-8573, Japan

**Faculty of Systems, Information and Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba-shi, Ibaraki 305-8573, Japan

Received:
March 20, 2013
Accepted:
June 28, 2013
Published:
September 20, 2013
Keywords:
fingernail detection, two-step searches, differences of distribution of nail-color pixels
Abstract

As far as we know, previous studies have only used color information for fingernail detection. Images of the palm, however, have a lot of pixels that have the same color values as the fingernail. Other kinds of some information are required to distinguish fingernails from areas of the palm having the same color. We found that there seem to be differences in the distribution of nail-color pixels, which is useful for fingernail detection especially when a camera captures a palm side. We found differences of the areas of the fingernail and skin, and have confirmed these are available for corresponding to the palm. In this paper, therefore, we propose a fingernail detection system using differences in the distribution of the nail-color pixels. The system proposed first fixes provisional nail color indicating nail-likelihood as a calibration process. In main processing, the system has two-step searches. In the first step, it detects all areas which have similar colors to the provisional nail color. Then, in the second step, it distinguishes fingernails from other areas using differences in distribution of nail-color pixels. In the experiments, we investigate the relationship between wrist rotation angles corresponding to the gradient of the nail and percentages of the correct detection. As a result, we confirm that our proposed system can detect only fingernails with at least 85% correct answer or more, except a camera is almost facing to the side of a little finger or thumb.

Cite this article as:
N. Fujishima and K. Hoshino, “Fingernail Detection System Using Differences of the Distribution of the Nail-Color Pixels,” J. Adv. Comput. Intell. Intell. Inform., Vol.17, No.5, pp. 739-745, 2013.
Data files:
References
  1. [1] K. Hoshino and T. Tanimoto, “Realtime Hand Posture Estimation with Self-Organizing Map for Stable Robot Control,” IEICE Trans. on information and systems, Vol.6, No.R89-D, pp. 1813-1819, 2006.
  2. [2] I. Oikonomidis, N. Kyriazis, and A. A. Argyros, “Efficient modelbased 3D tracking of hand articulations using Kinect,” Proc. of the 22nd British Machine Vision Conf. (BMVC), 2011.
  3. [3] A. Tsuda, H. Kato, A. Yoneyama, and S. Hangai, “Nail Art Simulation by Hue Difference Feature with Light,” Proc. of the 2009 IEICE General Conf., p. 290, 2009 (in Japanese).
  4. [4] Y. Chou and P. Bajcsy, “Toward face detection, pose estimation and human recognition from hyperspectral imagery,” National Center for Supercomputing Applications, Technical report TR. 20041108-1, 2004.
  5. [5] E. Tamaki and K. Hoshino, “Personalized color system for robust extraction of skin-color,” Trans. of the Virtual Reality Society of Japan, Vol.12, No.4, pp. 471-478, 2007 (in Japanese).
  6. [6] N. Fujishima and K. Hoshino, “Examination of Regions containing Color similar to that of Nails,” Proc. of the 19th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2013), pp. 78-83, 2013.

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Last updated on Feb. 18, 2019