The thesis project is aimed to automate ultrasonic Time-of-Flight (ToF) technique for saw log classification using signal processing. The ToF technique works in such a way that ultrasonic tone-burst pulses are sent into a saw log, and then the ToF that the pulses take for the propagation is measured and used to calculate the sound speed and further, the Modulus of Elasticity (MoE). Based on the MoE, the quality of the logs is predicted and presorted before sawing. Development of matched filters is the central task for automating the ToF technique.  The whole project was carried out in two different parts: 1) Fundamentals and MATLAB implementation, and 2) Real-time implementation based on digital signal processor.     In the first part, fundamentals on the ToF technique and matched filters have been studied, and then MATLAB simulations of matched filters for automating the technique have been made. After this, test measurements have been conducted. The test results are shown to be consistent with the simulation: matched filtering works well for automating the ToF technique. In the second part of the report, an embedded algorithm has been developed and implemented on a Digital Signal Processor. The algorithm is the first step in the automation of measurements. Eventually, two test measurements have been performed with the DSP. The results were obtained using both oscilloscope to visualize and MATLAB to plot the obtained debug log, and they have shown that the algorithm works, and can automatically measure the ToF, which is in turn used to calculate the sound speed and MoE. The further work on the project that needs to be done, is to applying the developed system to the real situations in sawmills, and improving it according to their requirements.