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A survey of automated visual inspection
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Robotics and Computer-Integrated Manufacturing
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AMS '08 Proceedings of the 2008 Second Asia International Conference on Modelling & Simulation (AMS)
Cascaded and hierarchical neural networks for classifying surface images of marble slabs
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews - Special issue on information reuse and integration
Automatic system for quality-based classification of marble textures
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Segmentation of abdominal organs from CT using a multi-level, hierarchical neural network strategy
Computer Methods and Programs in Biomedicine
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Although there are many industrial machines used in marble industry, classification of marble slabs in terms of quality is generally performed by human experts. Due to economic losses of this rather subjective process, automatic and computerized methods are needed in order to obtain reproducible and objective results in classification. With the aim of remedying this insufficiency in marble industry, a new electro-mechanical system, which automatically classifies marble slabs while they are on a conveyor belt and groups them with the help of a control mechanism, is proposed. The developed system is composed of two parts: the software part acquires digital images of marble slabs, extracts several features using these images, and finally performs the classification using clustering methods. The hardware part is composed of a conveyor belt, a serial port communication system, pneumatic pistons, a programmable logic controller (PLC), and its control circuits, all employed together for grouping the marble slabs mechanically. Although similar studies exist, this paper proposes three novelties over the existing systems. Firstly, a new hierarchical clustering approach is introduced for quality classification without requiring a training set. Secondly, a new feature set based on morphological properties of marble surface images is proposed. Finally, an electro-mechanical system is designed for accomplishing the task of sorting out the classified marble slabs. In the literature, only a system with a labeling mechanism has been presented. Our system, on the other hand, comes with a complete conveyor belt acting as an element that links the production line with the proposed system. This allows the possibility of embedding the proposed system into the production line of a marble factory. It has been observed that although the performance of the developed system is not as high as neural network based systems that use training, it could still be employed in industry when there is no available training set of samples. With this advantage, it provides an increase in the quality control standards of marble slab classification, since marbles are classified with an objective and uniform-through-time criterion.