In　this　paper,　we　present　a　saliency　guided　image　object　segment　method.　We　suppose　that　saliency　maps　can　indicate　informative　regions,　and　filter　out　background　in　images.　To　produce　perceptual　satisfactory　salient　objects,　we　use　our　bio-inspired　saliency　measure　which　integrating　three　factors:　dissimilarity,　spatial　distance　and　central　bias　to　compute　saliency　map.　Then　the　saliency　map　is　used　as　the　importance　map　in　the　salient　object　segment　method.　Experimental　results　demonstrate　that　our　method　outperforms　previous　saliency　detection　method,　yielding　higher　precision　(0.7669)　and　better　recall　rates　(0.825),　F-Measure　(0.7545),　when　evaluated　using　one　of　the　largest　publicly　available　data　sets.　©　Springer　International　Publishing　Switzerland　2014.