Beef freshness classification by using color analysis, multi-wavelet transformation, and artificial neural network

Any radiation techniques have been performed such as gamma radiation, X-ray, and infrared to determine the level of reduction in physical beef quality. The main difference of the techniques is the radiation wavelength exposure. One way to determine the level of beef freshness is by image processing. Image acquisition´s results in the form of 8 bits digital data at each base color RGB (Red, Green, Blue) is converted into the HSV (Hue, Saturation, Value) color space to see the difference of its brightness. The steps of classification process of beef freshness through image acquisition by using digital camera, pre-processing the image, and extracting its feature by using color analysis & multi-wavelet transformation. The last process is the classification process by using Nearest Neighbor & artificial neural network Back-propagation. This system can perform 75% accuracy by using NN classification with computation time in 10.683 second, while the best accuracy from using back-propagation is 71.4286% with the computation time 15.800086 second.