Since JPEG is the most widely used compression standard, detection of forgeries in JPEG images is necessary. In order to create a forged JPEG image, the image is usually loaded into a photo editing software, manipulated and then re-saved as JPEG. This yields to double JPEG compression artifacts, which can possibly reveal the forgery. Many techniques for the detection of double JPEG compressed images have been proposed. However, when the image is resized before the second compression step, the blocking artifacts of the first JPEG compression are destroyed. Therefore, most reported techniques for detecting double JPEG compression do not work for this case. In this paper, we propose a technique for detecting resized double JPEG compressed (called RD-JPEG) images. We first identify features that can discriminate RD-JPEG images from JPEG images and then use Support Vector Machines (SVM) as a classification tool. Experiments with many RD-JPEG images with different quality and scaling factors indicate that our technique works well.