The innovation work is to acquire distorted images information with height compensation. Computer vision allows observation of the surroundings. Generally, images collected from cameras in automated production lines are front views. But there is a certain angel between the camera and the working platform in limited space which will result in perspective distortion and make following works such as feature extraction and object recognition much more difficulty. Even more, it will reduce precision for grasping objects and production efficiency. For efficient considerations, correction of the distorted image has potential economic and social needs. Thus, we propose the combined method of Hough transformation and perspective transformation, which can convert the distorted image into a front view. In addition, we remove the effect of objects' height to improve positioning accuracy. Then we apply it to the Delta robot to correct the distorted image and recognize objects. It is important to note that the camera can be mounted in any position. Verification of the effectiveness of method is required for a final practical test of the experiment. The experimental results have proved the accuracy of this method well. Moreover, positioning accuracy can be easily improved by an average of more than 10 percent with the method of height compensation.