Content-based image retrieval is an important task in many practical applications. All the existing algorithms can be divided into two categories, the global methods and the local methods. These methods both have their own drawbacks. Every kind of image property equally contributes to image retrieval applications in global methods, and only some selected ones are used in local methods. Generally, the global methods can not fully represent the specific properties of user interest, and many image properties are lost in local methods. In this paper, a novel method has been proposed, in which image properties are assigned with different weights, denoting the importance of the property in image retrieval application. The represented method simulates human perception of image foreground, and can make a trade-off between global methods and local methods. Experiments show that this method can improve image retrieval performance, without the lost of simplicity and compactness.