In this paper, we propose method to easily conduct the wheel alignment measurement by using Camera Calibration and Laser Triangulation. By taking advantage of laser projection which is ubiquitous in structured environments, our method makes it convenient for a mobile operation to collect the data needed for calibration. The proposed method estimates the relative position of the wheel by first determining the pose of each plane of the wheel and by comparing to standard data; we can easily find the misalignment of the wheel. The algorithm is validated first by performing experiments on simulated data and investigating its sensitivity for measurement to noise.Index Terms-camera calibration, laser triangulation, alignment, angle measurement.
Object recognition is one of the problems in computer vision and so many techniques have come up to solve. All of them employ machine learning, because the computer has to learn first and use it in future to say whether the query image matched or not. These proposes approaches for object recognition by applying scale and rotation invariant feature transform in an automatic segmentation algorithms like FAST,SURF, SIFT,ORB etc. The features should be discrete and stable so that it can be used for matching an object in different views. At first, an object is trained to find best features. The object can be recognized in the other images by using achieved feature points. The results should show that the proposed approach is reliable for object detection and should be robust to the noise.
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