Abstract
This project is focusing on corrosion inspection using image. Inspection which have particularly challenging environmental conditions and characteristics, increase the complexity of the inspection operation. By using software image filter to enhance the image data, it is believe that the object recognition technique will be able to analyse the image data accurately. A few software filters have been identified in this works based on textural feature and colour progression factor that are the characteristic of image corrosion. Therefore, in order to obtain suitable software image filter, neural network is use for optimization. The experiment result shows among those identified image enhancement filters for visual corrosion inspection, Wavelet De-noising gives desirable result in terms of Mean Square Error, Peak Signal to Noise Ratio and Neural Network optimization.
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Idris, S.A., Jafar, F.A. (2015). Image Enhancement Filter Evaluation on Corrosion Visual Inspection. In: Sulaiman, H., Othman, M., Othman, M., Rahim, Y., Pee, N. (eds) Advanced Computer and Communication Engineering Technology. Lecture Notes in Electrical Engineering, vol 315. Springer, Cham. https://doi.org/10.1007/978-3-319-07674-4_61
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DOI: https://doi.org/10.1007/978-3-319-07674-4_61
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