Grayscale and Binary Image Enhancement of Hand Vein Images to Aid Peripheral Intravenous Access - Marlina, Yakno; Junita, Mohd Saleh; Bakhtiar, Affendi Rosdi (INASE, 2015)
Difficulty in achieving a peripheral intravenous (IV) access in pediatric and some adult’s patient is a clinical problem. The use of near-infrared imaging device to aid visualization of an IV access usually suffers from low contrast and noise due to nonillumination and thickness of hand skin. This further complicates subsequent processing such as image segmentation. In this work, two methods are proposed in two different stages; grayscale enhancement and binary enhancement for correction of low contrast and noisy images. For grayscale enhancement, a combination of histogrambased and fuzzy-based contrast enhancement algorithms are applied on hand vein images. For binary enhancement, a combination of three techniques; Artificial Neural Network pixel corrector, Binary Median Filter and Massive Noise Removal, are applied on the binary hand vein images. Comparative analysis on test images using different contrast enhancement methods has shown superior results from the proposed method in comparison to its counterparts.