Determination of Concrete Compressive Strength by Using Image Processing and Artificial Neural Network Methods

Nowadays, the practices of artificial intelligence methods on engineering science find solutions on engineering problems and become an alternative to methods and techniques used upon today by becoming widespread day by day. Image processing technology is also one of these artificial intelligence methods. Image processing involves many processes like obtaining, digitizing, enhancing of image. The use of image processing in construction engineering is also quite widespread. Various studies were made particularly on concrete technology and materials science. In this study, traditional testing methods used on identifying compressive strength of concrete were examined. In this context, a range of analytical modeling was practiced with digitizing image practice in order to see the performance of image processing technique as a new alternative testing method on identifying compressive strength of concrete. An analytical model on digitizing image has been occurred by using image processing and artificial neural networks together. The success of analytical modeling was examined by comparing with experimental data. In the result of the practice, it was seen that a high rate of accuracy was obtained. The constraints of use of image processing on material and structural engineering and the advantages of the method were discussed.