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We propose the Facial Trait Code (FTC) to encode human facial images. The proposed FTC is motivated by the discovery of some basic patterns existing in certain local facial features. We call these basic patterns Distinctive Trait Patterns (DTP), which can be extracted from a large number of faces. We have also found that the fusion of these DTP's can accurately capture the appearance of a face. The extraction of DTP involves clustering and boosting for maximizing the discrimination between human faces. The extracted DTP's can be symbolized and used to make up the n-ary facial trait codes. A given face can be encoded at some prescribed facial traits to render an n-ary facial trait code with each symbol in its codeword corresponding to the closest DTP. We applied FTC to a face identification and verification problems with 3575 facial images from 840 people under different illumination conditions, and it yielded satisfactory results.