Directional features have been successfully used for the recognition of both machine-printed and handwritten Kanji characters for the last decade. This paper attempts to explain why the directional features are effective. First, the advances of directional features and related methods are briefly reviewed. Then the properties that the similarity measure should hold are discussed and simulation experiments of directional pattern matching are conducted to validate the properties. This analysis is expected to inspire the design of new and more effective features.