• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.8
• /
• pp.1809-1818
• /
• 2010

In order to detect the skin color area from input images, many prior researches have divided an image into the pixels having a skin color and the other pixels. In a still image or videos, it is very difficult to exactly extract the skin pixels because lighting condition and makeup generate a various variations of skin color. In this thesis, we propose a method that improves its performance using hierarchical merging of 3D skin color model and context informations for the images having various difficulties. We first make 3D color histogram distributions using skin color pixels from many YCbCr color images and then divide the color space into 3 layers including skin color region(Skin), non-skin color region(Non-skin), skin color candidate region (Skinness). When we segment the skin color region from an image, skin color pixel and non-skin color pixels are determined to skin region and non-skin region respectively. If a pixel is belong to Skinness color region, the pixels are divided into skin region or non-skin region according to the context information of its neighbors. Our proposed method can help to efficiently segment the skin color regions from images having many distorted skin colors and similar skin colors.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1624-1624
• /
• 2001

Near-infrared spectroscopy (NIRS) was used to investigate the possibility for application in identification of apple cultivars. Three apple cultivars ‘Kamhong, Hwahong, and Fuji’ produced in Korea were scanned over the range of 1100-2500nm using NIRS (Infra Alzer 500). Two types of samples were used for scanning; one was apple with skin and the other was apple without skin. For cultivar identification, the NIR absorbance spectrums were analyzed by qualitative calibration in “Sesame” analysis program, and the various influence properties such as sugar contents, acidity, color, firmness, and micro-structure were compared in scanned samples. The ‘Kamhong’ cultivar could be identified from ‘Hwahong’ and ‘Fuji’ cultivars using the cluster model analysis. The test samples in calibration between ‘Kamhong’ and ‘Fuji’ cultivars could be completely identified. The test samples in calibration between ‘Kamhong’ and ‘Hwahong’ cultivars could be identified most of all. But, ‘Hwahong’ and ‘Fuji’ cultivars could not be quite classified each other. The apple skin influenced the identification process of apple cultivars. The samples without skin were more difficult to classify in calibration than the samples with skin. The physicochemical properties of apple cultivars showed like the result of identification in calibration using NIRS. Some physicochemical properties of ‘Kamhong’ cultivar were different from those of the other cultivars. Those of ‘Hwahong’ and ‘Fuji’ cultivars showed. similar to each other. The sucrose contents of ‘Kamhong’ cultivar were higher and the fructose contents and firmness of skin and flesh were lower than those of the others. The hypodermis layer of skin in ‘Kamhong’ cultivar was thinner than those of the others. In this studies, the identification of all apple cultivars by NIRS was not quite accurate because of the physicochemical properties which were different in the same cultivar, and inconsistent patterns by culivars in some properties. To solve these problems in NIRS application for apple cultivar identification, further study should be focused on the use of peculiar properties among the apple cultivars.