Research on Parallel Mining Method of Massive Image Data Based on AI

Parallel mining of image data is based on the extraction of internal rules and detail features of image. Combined with image edge detection to realize parallel mining of image data, a parallel mining algorithm of image data based on AI is proposed. Firstly, the multidimensional parallel eigenvalues of image data are extracted by the gray feature extraction algorithm of massive images, and then the template matching and information fusion of massive image data are carried out by using Map/Reduce model. According to the matching results, the parallel mining results of image data are obtained. Finally, the simulation experiment of image data parallel mining is realized by using Matlab software. The results show that compared with other image data parallel mining algorithms, this algorithm reduces the parallel mining time of image data and improves the speed of image data parallel mining, especially for large-scale image data parallel mining.