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There are many biotechnological applications where 3-dimensional objects are represented as 2-d objects in a digital image. The dynamic and variable nature of the microorganism thus creates a formidable challenge to the design of a robust 2-d image inspection system with the ideal characteristics of high analysis accuracy but wide generalization ability. We have developed a novel case-based object recognition method for this kind of problems. The method is able to recognize objects and learn incrementally cases for the recognition process. Such a procedure requires capturing new cases for the further recognition process in order to be able to handle the variability of the natural objects. We describe the theory behind the method and how it works on our problem of fungi spore recognition. The developed case-based object recognition method is flexible and robust enough to be used for different recognition tasks in biotechnology.

Case-Based Object Recognition with Application to Biological Images