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Automatically assigning one or more relevant keywords to image has important significance. It is easier for people to retrieve and understand large collections of image data. Recent years much research has focused upon this field. In this paper, we introduce a salient region detection and segmentation algorithm used for image retrieval and keywords auto-annotation. We investigate the properties of a bin-cross bin metric between two feather-vectors called the Earth Mover's Distance (EMD), to enhance the precision and recall performance. The EMD is based on a solution to the transportation problem from linear optimization. It is more robust than histogram matching techniques. In this paper we only focus on applications about color-feathers, and we compare the performances about image auto-annotation and retrieval between EMD and other histogram matching distances. The results indicate that our methods are more flexible and reliable.