Simulation of Computer Image Processing Model Based on Random Forest Algorithm
Haotian Liu · 2023
In essence, image recognition, as a pattern classification problem, can also be processed by classical pattern classification algorithms. Under the background of network information technology, it is need to use computer vision algorithm to process the image and realize the three-dimensional reconstruction of the image for the distortion of the true three-dimensional display image of intelligent interactive system. Random Forest (RF) is a new ensemble learning algorithm developed in recent years, which has good classification accuracy. In this article, a computer image processing model based on RF algorithm is proposed to enhance the ability of depth feature learning. The experimental results show that this image processing technology is more accurate than BP neural network and can be widely used in image processing. High-level target feature representation can often improve the recognition accuracy. However, the extraction of high-level target features generally has certain computational complexity. Compared with traditional methods, the accuracy of the proposed method is greatly improved, and the generalization performance is superior, which can identify images that have been beautified and repaired.