|Ramalingam, N - OSU|
|Ling, P - OSU|
Submitted to: ASAE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: May 1, 2002
Publication Date: July 28, 2002
Citation: Ramalingam, N., Ling, P.P., Derksen, R.C. 2002. Dynamic Segmentation for Automatic Spray Deposits Analysis on Uneven Leaf Surfaces. ASAE Annual International Meeting. Paper No. 023096. Technical Abstract: Characterizing spray deposits on target surfaces can aid in determining the factors leading to the failure of some pesticide applications. Spray coverage evaluation on leaf surfaces is usually a very subjective process, made more difficult by variations in leaf surface morphology and lighting conditions. The objectives of this study were to implement and evaluate four different dynamic thresholding algorithms that could increase the efficiency of spray coverage measurements on leaf surfaces and reduce reliance on subjective operator judgements. The algorithms were evaluated for accuracy to effectively segment the images that had non-uniform contrast between the droplets and the leaf background, and with varying intensities of the fluorescent tracer over uneven leaf surfaces. The analysis included segmentation of the droplets, estimation of droplet area and the total number of different size and shape droplet deposits on a leaf surface. Guidelines for selecting a suitable dynamic thresholding technique for given image characteristics are proposed. A two-pass approach was evaluated wherin the images were first thresholded by the best general purpose technique to compute the blob characteristics, based on which an image specific thresholding algorithm was applied as the second pass for improved accuracy. The experimental results identify techniques that will aid in the objective evaluation of spray coverage on leaf surfaces. Implementing these techniques will provide manufacturers and growers with more confidence in reported results and will increase the speed in which coverage evaluations can be made and reported.