Computer-aided image recognition methods are non-invasive, easy to implement and quick to calculate defects detection methods. They seem to be a promising method for investment casting applications – defects can be detected in individual incestment casting processes, reducing the costs caused by defective castings.As part of the research, defects have been defined and described in wax models. For each of the disadvantages, a characteristic signature was created allowing for its later detection in the image. In the next stage pre-processing of models was carried out, including segmentation, denoising and sharpening in order to prepare images for the input form for the algorithm. Next, an algorithm for searching and classifying areas containing separate defects and deviations from correct images was developed. The algorithm uses statistical classification methods and machine learning elements using convolutional neural networks.Keywords: Investment casting, wax model, image recognition, neural networks
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