Paper
7 March 2014 Improved wheal detection from skin prick test images
Author Affiliations +
Proceedings Volume 9024, Image Processing: Machine Vision Applications VII; 90240J (2014) https://doi.org/10.1117/12.2038442
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States
Abstract
Skin prick test is a commonly used method for diagnosis of allergic diseases (e.g., pollen allergy, food allergy, etc.) in allergy clinics. The results of this test are erythema and wheal provoked on the skin where the test is applied. The sensitivity of the patient against a specific allergen is determined by the physical size of the wheal, which can be estimated from images captured by digital cameras. Accurate wheal detection from these images is an important step for precise estimation of wheal size. In this paper, we propose a method for improved wheal detection on prick test images captured by digital cameras. Our method operates by first localizing the test region by detecting calibration marks drawn on the skin. The luminance variation across the localized region is eliminated by applying a color transformation from RGB to YCbCr and discarding the luminance channel. We enhance the contrast of the captured images for the purpose of wheal detection by performing principal component analysis on the blue-difference (Cb) and red-difference (Cr) color channels. We finally, perform morphological operations on the contrast enhanced image to detect the wheal on the image plane. Our experiments performed on images acquired from 36 different patients show the efficiency of the proposed method for wheal detection from skin prick test images captured in an uncontrolled environment.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Orhan Bulan "Improved wheal detection from skin prick test images", Proc. SPIE 9024, Image Processing: Machine Vision Applications VII, 90240J (7 March 2014); https://doi.org/10.1117/12.2038442
Lens.org Logo
CITATIONS
Cited by 6 scholarly publications and 2 patents.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Skin

Chromium

Calibration

Principal component analysis

RGB color model

Detection and tracking algorithms

Image contrast enhancement

RELATED CONTENT


Back to Top