Images, in contrast to text, represent an effective and natural communication media for humans, due to their immediacy and the easy way to understand the image content. Shape recognition and pattern recognition are one of the most important tasks in the image processing. Crime scene photos should always be in focus and there should always be a ruler be present, this will allow the investigators the ability to resize the image to accurately reconstruct the scene. Therefore, the camera must be on a grounded platform such as tripod. Due to the rotation of the camera around the camera center there exist the distortion in the image which must be minimized. The distorted image should be corrected using transformation method. Deze taak is nogal uitdagend en essentieel omdat elke verandering in de afbeeldingen kan misidentificeren een object voor onderzoekers.

Forensic image processing can help the analyst extract information from low quality, noisy image or geometrically distorted. Obviously, the desired information must be present in the image although it may not be apparent or visible. Considering challenges in complex forensic investigation, we understand the importance and sensitivity of data in a forensic images.The HT is an effective technique for detecting and finding the images within noise. It is a typical method to detect or segment geometry objects from images. Specifically, the straight-line detection case has been ingeniously exploited in several applications. The main advantage of the HT technique is that it is tolerant of gaps in feature boundary descriptions and is relatively unaffected by image noise. The HT and its extensions constitute a popular and robust method for extracting analytic curves. HT   attracted a lot of research efforts over the decades. The main motivations behind such interest are the noise immunity, the ability to deal with occlusion, and the expandability of the transform. Many variations of it have evolved. They cover a whole spectrum of shape detection from lines to irregular shapes.

This master thesis presents a contribution in the field of forensic image processing. Two different approaches, Hough Line Transformation (HLT), Hough Circular Transformation (HCT) are followed to address this problem. Fout estimatie en validatie is gedaan met de hulp van root mean square method. De prestatie van beide methoden is geëvalueerd door ze te vergelijken. We present our solution as an application to the MATLAB environment, specifically designed to be used as a forensic tool for forensic images.