We address the problem of approximate pattern matching using the Levenshtein distance. Given a text T and a pattern P , find all locations in T that differ by at most k errors from P . For that purpose, we propose a filtration algorithm that is based on a novel type of seeds, combining exact parts and parts with a fixed number of errors. Experimental tests show that the method is specifically well-suited for short patterns with a large number of errors