An Assistant Recognition Method Based on Multi-Scale Feature Algorithm

The auxiliary recognition method based on multi-scale feature algorithms is a technology used to improve the accuracy of image recognition. Traditional image recognition algorithms often face difficulties in processing images with rich details, as changes in details may lead to difficulty in feature extraction and a decrease in accuracy. To overcome this problem, multi-scale feature algorithms have been introduced, which can analyze images at different scales and capture feature information at different levels. The Committed step of this method include the following aspects: First, the original image is divided into multiple sub images of different scales by using image pyramid technology. Then, for each sub image, feature extraction algorithms are used to extract its feature representation. These features can be local features, global features, or mixed features, selected according to specific application requirements. Next, by fusing features at different scales, a comprehensive feature representation is obtained. Finally, this feature representation can be used for image recognition tasks such as object detection, classification, etc.