Object Recognition has been one of the most increasingly important issues in Image Processing, finding applications in Computer Vision, Photography, Multimedia Retrieval, Detection and Data Classification. Based on the bag-of-words model, we demonstrate the efficiency of an advanced algorithm capable of performing objet recognition for both indoor and outdoor images. We use SIFT for retrieving objects’ local features, k-means Clustering for Codebook formation, train the system with SVM using some manually labeled images, and test the it with similar data set.