Abstract: The field of medical imaging sciences has ever been growing over the past couple of decades in terms of its vast database, which may itself seem to be detrimental towards the radiologists and physicians because of the very reason that they may be unable to distinguish and interpret the images amongst the others. Thus, the need of the automated view classification, detection of orientation and the diagnosis of diseases is very much inevitable, which can be employable by means of the state-of-the-art decision making algorithms in the modern era of computational excellence. In this work, X-ray images of six different classes namely chest, skull, foot, palm, spine and neck with different position namely anterior view, lateral view and oblique view have been taken. The position of the X-ray images are automatically detected using speed up Robust Features and Harris corner detector algorithm, out of which SURF out performing Harris corner detector with an accuracy of 95.22%

Keywords: X-ray images, M3 filter, anterior-posterior view, lateral view, oblique view, Speed Up Robust Features (SURF), Harris corner detector.