Recognition of Natural and Non-Natural Defects Presented in Ophthalmic Lenses

This paper is concerned with the design of a classification system based on artificial neural networks to distinguish between natural and non-natural cosmetic defects found in ophthalmic lenses. Natural cosmetic defects are related to small cotton fabrics, and non-natural defects are formed during the fabrication process. A set of geometric, morphology and topologic features are defined in order to represent these defects. The recognition problem of theses defects is faced with feedforward and SOM artificial neural networks paradigms. The performance of the feedforward and SOM networks turned to be similar, 92.35% of correct classification. The performance of these neural networks is acceptable compared against the performance of a human inspector considering that a human inspector reaches a performance between 85% and 90%. Besides, the ANN approach is completely free of changes in its decision, contrary to a human inspector that can change his/her mind due to subjective influences.