The SIFT algorithm is widely adopted by researchers in image and graphic study

with its many advantages such as invariance to scaling

rotation

noise and illumination changes. SIFT feature is based on local gradient

making it invulnerable to large scale of image extension

compression and rotation

and this meets the practical requirements of 3D object recognition. And the sensitivity to homographic transformation of the feature can be applied to partition the view space. Reasonably setting the threshold value

SIFT algorithm can handle the technical problems such as cutting the object from its background. After pre-processing

the high computation complexity can be reduced

making the system run in real time. Therefore

applying SIFT feature in view space partition

cutting the object from its background and pattern matching can effectively enhance the robustness of the system and improve its speed and efficiency.