الفهرس 
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Abstract
The economic environment in the industry has changed over the last years. The focus on the production floor has moved from increasing capacity to improving the production. One major consequence of this shift in focus has been increased interest in X-ray inspection. Standard x-ray inspection system depends heavily on the operator’s ability to manipulate the controls to obtain the best possible image. Once the image is obtained, the next hurdle is the operator’s ability to interpret the image and make decisions to improve the manufacturing processes. However, the image that the operator deals with and analyzes is based on what the operator is able to see initially. Often, extraneous factors such as lack of experience, fatigue or work environment will adversely affect the operator’s ability. These factors result in longer inspection durations and inconsistent decisions across operators, which have major cost implications in the production context. Thus, for maximizing output from the x-ray system is to take the right decision for this image, irrespective of the operator’s ability. This work introduced in this theses depends upon computer vision system as a tool, Image processing as a technique and Visual Basic as a programming language to have a prototype of visual system, which is capable of inspecting tires and make the decision. The system introduced Automatic Defect Recognition System (ADRS) Software that automatically optimizes x-ray images. This system enhance the image in a single path, and then calculate some statistical through this system to the enhancement image and shows all defects clearly. The system was verified and compared with actual results, and the results showed a good accuracy for the introduced system.