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As grasping online products with unfixed location from the conveyor belt and placing them to the fixed position with the decided posture by the intelligent Manipulator usually need complex visual image processing and high cost of the intelligent Manipulator system, a visual recognition technology based on auxiliary positioning device was proposed. Firstly, with the Apple Mobile Phone as the specific research object, under non-extreme lighting conditions, 44 mobile phone images of 11 groups under different illumination conditions were collected and were pre-processed. Secondly, according to the grayscale distribution characteristics of histogram of each image, though research on the changing situation of the grayscale value with the maximum number of gray values and the mean of the gray value of all pixels for each image, the piecewise linear threshold segmentation criterion was induced. Finally, the right targets were found by applying area characteristic, and the position feature of the target is used to identify the image, and then the characteristic recognition algorithm were induced. With ordinary video camera as the experimental equipment, an algorithm adaptability experiment was implemented. The experimental results show that the visual approach can identify mobile posture stably and reliably under the non-extreme lighting condition and the stable light source environment. The recognition technology is more than 50% lower in cost than the multi-degree-of-freedom manipulator + camera recognition method, which can be widely used in the production line of the shape products of mobile phones.