Abstract : This paper describes damaged character pattern recognition on wooden tablets excavated from the Heijyo palace site (the ancient palace in the Nara period from AD. 710 to 794). Since most of excavated tablets have been stained, damaged, and sometimes broken into pieces, it is extremely difficult even for archaeologists to read characters from badly blurred or missing ink on tablets. The aim of the character recognition is to output candidates even for degraded or partially lost character patterns in order to give hints to human expert readers rather than to read handwritten characters at the maximum speed. We propose a method that applies nonlinear normalization and feature extraction for ternary character pattern images with gray missing area supplemented by readers. The proposed method realizes 60.2% as the 10th cumulative rate for 2,108 character patterns extracted from wooden tablets with partial damages applied artificially. This result is better than the result of the previous method.