Saliency　has　been　widely　applied　to　detecting　the　most　attractive　object　in　an　image.　This　paper　presents　a　novel　method　based　on　saliency　map　for　object　localization　in　an　image.　We　regard　saliency　map　computation　as　a　preprocessing　step,　which　is　obtained　using　a　discriminative　regional　feature　integration　approach.　Then,　the　saliency　map　is　processed　to　highlight　more　saliency　contour　and　remove　some　subordinately　salient　points　using　region-growsegmentation　algorithm.　Finally,　saliency　object　is　located　with　efficient　sub-window　search　algorithm　(ESS)　in　the　binarized　saliency　map.　This　approach　is　able　to　identify　the　exact　location　and　roughly　the　size　of　saliency　object　in　an　image.　The　performance　evaluation　using　MSRA-B　dataset　demonstrates　our　approach　performs　well　in　object　localization　in　images.