Amrane, AbdesalamMeziane, AbdelkrimBoulekrinat, HoudaAtik, Ali2017-04-102017-04-102017-05-11http://dl.cerist.dz/handle/CERIST/884Object localization plays an important role in object detection and classification. In the last years, several methods have shifted from sliding windows techniques to object proposals techniques. The latter produces a small set of windows submitted to an object classifier to reduce the computational time. In this paper, we propose a fast unsupervised method that combines the edge feature and saliency map to generate less than hundred bounding boxes from the processed image. Our approach exploits a number of rules based on edges information plus saliency regions to decide if an object is present in a window. We have carried out several experiments to validate our approach on ImageNet dataset and obtained very promising results.Object proposalsBounding boxObject detectionSaliency mapSliding windowTechnical ReportCERIST-DSISM/RR-17-00000007--DZ