Image analyzation method with unrecognized object memory mechanism

Abstract

An image analyzation method with an unrecognized object memory mechanism are provided. Initially, whether a target object belongs to a known category using an object recognition model is determined; if not, then the object memory mechanism is executed. The mechanism first obtains image feature information through a feature extraction algorithm, and generates an attention representative value by a feature classifier. The target objects are grouped according to the numerical range it belongs to and stored in corresponding specified directories. When the number of target images in a directory reaches a quantity threshold, a new category label is assigned to the target images and used as retraining data for the object recognition model. The image analyzation method classifies unrecognized objects and enables the object recognition model to recognize unrecognized objects through learning, without the need for manual labeling of unrecognized objects, thereby saving resources and cost.