This paper presents a face feature representation method based on image decomposition (FRID). FRID first decomposes an image into a series of orientation sub-images by executing multiple orientations operator. Then, each orientation sub-image is decomposed into a real part image and an imaginary part image by applying Euler mapping operator. For each real and imaginary part image, FRID divides them into multiple non-overlapping local blocks. The real and imaginary part histograms are calculated by accumulating the number of different values of image blocks respectively. All the real and imaginary part histograms of an image are concatenated into a super-vector. Finally, the dimensionality of the super-vector is reduced by linear discriminant analysis to yield a low-dimensional, compact, and discriminative representation. Experimental results show that FRID achieves better results in comparison with state-of-the-art methods, and is the most stable method.