Application and effect simulation of image recognition technology based on machine vision feature parameters in art teaching

Under the new era background, the multi-cultures of various countries in the world are spreading and infiltrating each other, and the art education at this stage is in the stage of innovation and development. It is necessary to improve the teaching content and teaching methods of schools in an all-round way, deepen the research of education curriculum reform, especially to combine these new technologies with art classroom teaching to achieve the transformation of humanity. Today, with the great development trend of visual media, it has gradually entered the era of reading and map reading, which is a period of information flow and communication. The basic function of image is to transfer and convey image information. Therefore, in art teaching, it and graphics are complementary. In order to fully carry out art teaching, this paper applies the image recognition technology of machine vision feature parameters to art teaching and effect simulation. Machine vision technology analyzes the required resolution and color scale from digital imaging and uses preprocessed images and features to lock the images in the machine vision system, obtain the texture and proportion of art images according to the area, width and proportion of objects and complete classification and recognition. The whole image production process is more efficient, and finally can produce high-resolution art images. The results show that, due to the application of image recognition technology of machine vision feature parameters in art teaching and effect simulation, it has achieved good performance results. It has maximized the image recognition methods of students, thus cultivating students' artistic perception through artistic literacy, and promoting the balanced development of students.