<p>Rock quality designation (RQD) value is one of the essential indexes in rock mass quality evaluation. Currently, the identification and calculation of the RQD value mainly rely on manual operation, which is labor-intensive, costly, and inefficient. In view of the limitation of RQD value recognition calculation, this paper employs digital image processing technology to achieve the automatic recognition of the RQD value of drilling cores. Initially, the core images with angular deviation taken at the work site are geometrically transformed and corrected, and the external environment is removed except for the core box, and the image viewing angle is corrected. Subsequently, connected components are accurately identified and marked based on binarized images. Ultimately, all the marked lengths are obtained, and the total length value of the connected components is statistically identified, and the RQD value of the drilling core is calculated. Among these, the autonomous crack calibration method is used to deal with complex joint crack structures with small pixel differences, thereby enhancing the accuracy of RQD value recognition and calculation. The verification results demonstrate that the average relative error of the data obtained is approximately 3% by the automatic RQD value recognition method proposed in this paper. This research provides an approach and technical means for RQD value statistics, promotes the automation development of rock mass mechanical parameter determination, and offers efficient technical support for mine engineering design and practice.</p>