Salient objects detection in time sequenced images has a very important role in many applications such as surveillance systems, tracking and recognition systems, scene analysis and so on. This paper presents a novel approach for salient objects detection in time sequenced images. The approach in this paper is based on a visual saliency model which is proposed for analysis in time sequenced images. The model in this paper is based on a bottom-up visual saliency model which is presented by Itti in 1998. Multi different features are introduced to describe salient objects globally in time sequenced images. And they are combined into a single saliency map. Salient objects in time sequenced images can be detected by the final saliency map. The detection algorithm is unsupervised and fast. The results of the experiments indicate that our approach is effective and very robust to noise, blur, contrast level and brightness level.