The research of digital image processing and recognition began in 1965. Compared with analog images, digital images have great advantages such as convenient storage, transmission and compression, easy distortion during transmission and convenient processing, which provides a strong impetus for the development of image recognition technology. Object recognition mainly refers to the perception and understanding of objects and environments in the three-dimensional world, which belongs to the category of advanced computer vision. Based on digital image processing and recognition, combined with the research direction of artificial intelligence, systematics and other disciplines, its research results are widely used in various industries and detection robots. One of the shortcomings of modern image recognition technology is poor adaptive performance. Once the target image is polluted by strong noise or the target image is seriously incomplete, ideal results are often not obtained.
The mathematical essence of image recognition belongs to the mapping problem from pattern space to category space. At present, in the development of image recognition, there are three main recognition methods: statistical pattern recognition, structural pattern recognition and fuzzy pattern recognition. Image segmentation is a key technology in image processing. Since 1970s, it has been studied for decades and has been highly valued by people. Up to now, thousands of segmentation algorithms have been proposed with the help of various theories, and the research in this field is still being actively carried out.
There are many existing image segmentation methods, such as threshold segmentation, edge detection, region extraction, segmentation combined with specific theoretical tools and so on. According to the types of images, there are gray image segmentation, color image segmentation and texture image segmentation. As early as 1965, an edge detection operator was proposed, which led to many classical algorithms for edge detection. However, in recent twenty years, with the rapid development of image segmentation methods, computing technology and VLSI technology based on histogram and wavelet transform, the research of image processing has made great progress. Image segmentation method combines some specific theories, methods and tools, such as image segmentation based on mathematical morphology, image segmentation based on wavelet transform and image segmentation based on genetic algorithm.