抄録
This project is focusing on enhance image for visual corrosion inspection. Corrosion inspection which have particularly challenging environmental conditions and characteristics, increases 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 evaluate 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 characteristics of image corrosion. Therefore, in order to obtain the best image enhancement, neural network is use for optimization. The optimizations of wavelet de-noising filter via network to enhance images, were used for analysis of multi filter network for visual corrosion inspection image. The analysis outcome shows visual corrosion inspection image can be enhanced using multi filter network, and gives desirable result in terms of Mean Square Error and Peak Signal to Noise Ratio.
