A fast sequential method for polygonal approximation of digitized curves
Computer Vision, Graphics, and Image Processing
Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of image registration techniques
ACM Computing Surveys (CSUR)
Unsupervised learning of probabilistic concept hierarchies
Machine Learning and Its Applications
Different Learning Strategies in a Case-Based Reasoning System for Image Interpretation
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
Approaches to conceptual clustering
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Case-based object recognition for airborne fungi recognition
Artificial Intelligence in Medicine
Data mining on multimedia data
Data mining on multimedia data
Automatic target recognition by matching oriented edge pixels
IEEE Transactions on Image Processing
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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.