The inspection and monitoring of the wear of grinding tools is essential to ensure the quality of the grinding tool surface and the finished product. Most of the current methods for examining a grinding tool surface rely on dismounting the grinding tool. Often, the state of the grinding tool surface is checked indirectly by evaluating the quality of the workpiece. We describe the application of image processing, which offers an effective means for in situ inspection and monitoring. It yields more detailed information about the surface and the kind of wear observed than the common methods. By using multidirectional illumination and image fusion, an image with a high degree of relevant information is generated that is then segmented using the wavelet transform (multiscale analysis) and classified to distinguish grains and cavities on the surface. Results of the application of the algorithms for a high-performance grinding tool with CBN grains embedded in a resin base are presented.