A disease spot segmentation method using comprehensive color feature with multi-resolution channel and region growing

Abstract

The paper proposes a novel method to segment disease spots in leaves using image processing techniques. In the process of disease spot segmentation many challenges are faced such as uneven illumination and clutter background. To solve uneven illumination, color spaces and gray scale conversions are summed. Color spaces like H (hue) component of HSV, L*a*b* color spaces and Excess Red index (ExR) are used. Color to gray scale conversion is done by using weighted mulitresolution channel. Region growing method is used to solve the clutter background issues by interactively selecting growing seeds under real field conditions. Using precision, performance measure is calculated and an average segmentation accuracy of 94% is achieved.