Surface irrigation based on image object detection and fuzzy pid control

In recent years, image object detection has been highly concerned in various fields, especially in the industrial and academic fields. In addition, it also plays an important role in the field of computer. The solution of this problem is helpful to make a breakthrough in various visual tasks. In this paper, a saliency detection model based on ant colony optimization algorithm is proposed. Firstly, the input image is transformed into an undirected graph with different nodes by multi-scale super-pixel segmentation; secondly, based on the optimal feature selection strategy, the low contrast image contains significant target feature information and discards redundant noise information; then, the spatial contrast strategy is introduced to explore the global significance clues with relatively high contrast in the image. At the same time, in view of the current reality and considerations of agricultural surface irrigation, this paper finally selects an urban surface irrigation technology exhibition as the research sample to try to find the key problems involved. For the current situation is to make some suggestions, so that the current technology can be further applied in the development of agricultural surface irrigation. When ΔKP rule base of traditional fuzzy pid control algorithm is used for online correction of KP parameters, there is the problem of insufficient accuracy. This paper puts forward the optimized fuzzy pid algorithm of ΔKP rule base and studies its control performance. Compared with pid and traditional fuzzy pid, the control performance of the improved fuzzy pid controller can be improved by 18.62% and 32.61% respectively. In this paper, the image target detection technology is used to study the general situation of surface irrigation and the content of fuzzy pid control, in order to promote its vigorous development. © 2021, Saudi Society for Geosciences.