Bernier, T. and Landry, J.
2000 Canadian Agricultural Engineering, 42:101-109
Bernier, T. and Landry, J., (2000), "Algorithmic recognition of biological objects", Canadian Agricultural Engineering, 42:101-109.
Abstract:
An algorithmic method of object recognition to identify and count fungal spores in microscopic digital images is presented. The development of this process is a key element and cornerstone of a large-scale research program ultimately aimed at reducing fungicide application. The program, as a whole, is an attempt to build a machine based system in order to improve the ability of researchers to assess the population of pathogenic fungi within agricultural crops and thus more accurately target fungal pests. A three pass method was used: a preliminary pass in order to narrow the search space down to only the areas that contain spore-like darkening; a second pass that highlights both the center and the surrounding edge of the spore and produces a secondary image; and a third pass in which a template is matched to the secondary image. After the final pass, the list of positions and orientations of spores is reviewed and the conflicting and less likely positions are eliminated. The goal of the method is to accurately count the spores in the minimum amount of time. The resulting time is between 0 and 21 s of analysis on a 100 Mhz Pentium computer for a 64 by 64 pixel image. The algorithm, as implemented, demonstrated an accuracy of ¡À 5.3% on low quality images, which is less than the assumed error of humans performing the same task and is tolerant of partial occlusion. The system is loosely based on biological vision, is extremely versatile, and could be adapted for the recognition of virtually any object in a digitized ima ge.
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