Information techniques featuring adaptability, autonomy, and diversity found in the behavior of livings are promising. The purpose of this study is to explore object selection method adaptable to unexpected change of the environment. An attractor selection is used as an algorithm for flexible adjustment to various change of the environment. An attractor is a convergence point in a state space and corresponds to a stable point of a given system. The attractor selection chooses an attractor according to the suitability for a given environmental condition. The proposed object selection algorithm finds a solution from several images captured with different focus settings. To obtain these images a compound-eye imaging system is assumed to be used. In the object selection, an object is regarded as an attractor. The location and the features of the object are expressed as variables in the state space. In this study, hue in the Hue-Saturation-Value color model is used as a parameter of an environmental condition. In the simulation, two objects of different hue were located at different distances. One of the objects might be selected by the proposed algorithm. The correct operations of the algorithm are confirmed. The results show that the attentive object is correctly switched according to the change of selecting condition. The adaptability and the robustness of the method has been confirmed.