This study develops an image processing application to automatically detect the ripeness level of tomatoes using the YCbCr color space transformation. This method is effective because it is able to separate the luminance and chrominance components, so it can identify color changes that indicate the ripeness level of tomatoes, namely unripe, semi-ripe, and ripe tomatoes. The application is designed with matlab and uses a GUI interface that makes it easy for users to upload and process images. Based on trials on image samples, the system is able to classify tomato ripeness with 100% accuracy on a limited test dataset. The classification process is based on three main parameters: the red area ratio, the average value of the Cr channel, and the average value of the Cb channel. The results of the study indicate that this approach can be used as a digital solution in the automatic and efficient tomato sorting process
