Research on intelligent visual image feature region acquisition algorithm in Internet of Things framework

Abstract

In order to solve the problem that traditional technology is vulnerable to external interference, the visual features are missing, which affects the image feature region acquisition results, and can only be applied to the visual features of color features. This paper proposes an intelligent visual image feature region acquisition algorithm under the Internet of Things framework. This article describes the distribution of vision sensors in the Internet of Things. The IoT vision sensor acquires the experimental image. After the image is smoothed by the neighborhood average method, the inverse process differentiation of the integration is used to sharpen the edge of the image and enhance the sharpness of the image The noise interference of the image is excluded by the adjacent region average method and the differential method. In order to obtain feature region detection results clear and accurate, the agglomerative clustering algorithm sharpens the image, and the image edge list is obtained. Finally, the image stable extreme value area is determined, and the image feature region can be acquired in the stable extreme value area. In the stable extreme region, the SURF algorithm is used to detect the visual characteristic points, and the intelligent visual characteristic regions are collected through the Euler distance. It can be seen from the experiment that the image feature region of the algorithm has high acquisition precision, low mismatch rate, and fast acquisition speed.