Coronary arteries are the main arteries in human body that feed the heart muscle with blood. Coronary artery disease is one of the main causes of death around the world. One of the ways for cardiologists to diagnose this disease is to use x-ray angiography. In this method a hollow tube called catheter is inserted into an artery from the groin, neck or arm and threaded to the heart. After reaching the coronary arteries, the contrast agent is injected and a sequence of the heart pumping is captured using x-ray imaging. Cardiologists diagnose the stenosis or narrowness of arteries by watching these videos. These image sequences usually have low quality due to some artifacts such as low contrast, non-uniform illumination, presence of other body tissues, presenceof catheter, etc. During the last decades several image processing methods were proposed for enhancement of these images and segmentation of coronary arteries. In this thesis three methods are proposed. First of all, a method for coronary arteries region extraction is proposed. In this method at first a better vesselness map is obtained in the pre-processing stage, then in the feature extraction stage by using new modified edge detector a proper feature for vessel region in the obtained vesselness map is computed. Finally in the last stage the vessel region is extracted using block processing by considering the vessel feature. By finding the vessel region, the background region is weakened and in this way the visual quality of these images is enhanced. In the second proposed method, a new catheter detection method is proposed. In this method at first all the frames in a sequence are processed in order to reduce their artifacts and in the next stage each frame’s ridges are detected.In the last stage the catheter ridge in the first frame is detected and a second order polynomial is fit on it. After detecting the catheter in the first frame, because of the displacement of the catheterin the second frame due to the movements of the camera and body, the second order polynomial parameters in the first frame are used as initial values for finding the catheter. This procedure is repeated for all the frames in a sequence. In the last proposed method, a coronary arteries segmentation method is proposed which is based on superpixels. In this method the intensity values of the contrast enhanced image and vesselness map are used for deciding which superpixels belong to the arteries. By finding the orthogonal line on each pixel of the vessel ridge, the initial result of candidate vessel superpixels is modified. Also in order to reduce the false positive error of the proposed segmentation, the proposed catheter detection is used. These proposed methods are evaluated subjectively and objectively on angiograms. Keywords: Catheter,Enhancement, Coronary arteries, Ridge,Segmentation, X-ray angiography.