a design for a high reliability recognition system utilizes two optimized thresholds for each class k of a prototype data base . one threshold is a class region threshold cr k and the other is a dis - ambiguity threshold da k . cr k specifies a constrained region belonging to a class k , and da k corresponds to a value with which a sample belonging to class k can be correctly recognized with a high level of confidence . during recognition , if the distance d between an input sample x and the representative prototype r m of a nearest class m is larger than the class region threshold cr m , x will be rejected . furthermore , if the distance d is subtracted from the distance d between x and the representative prototype r s of a second nearest class s , the resulting distance difference must be greater than the dis - ambiguity threshold da m , or x will be rejected . an inventive algorithm is used to compute optimum thresholds cr k and da k for each class k . the algorithm is based on minimizing a cost function of a recognition error analysis . experiments were performed to verify the feasibility and effectiveness of the inventive method .