What is the relationship between the recognition efficiency of traditional image recognition?

1. Image features: Different types of images have different features, and some images with obvious features are easier to identify.

2. Classification algorithm: The classification algorithm used in traditional image recognition is usually based on machine learning or artificial neural network. Different algorithms will have different image processing methods and recognition effects.

3. Computational resources: Traditional image recognition needs a lot of computational resources for feature extraction, model training and classification reasoning. The performance and storage capacity of computer will directly determine the efficiency and accuracy of recognition.

4. Data set quality: It is very important to establish a high-quality image data set to improve the recognition efficiency and accuracy. The size, quality and diversity of data sets will affect the training effect and testing effect.

5. Environmental factors: Environmental factors such as illumination, angle and occlusion will also have a certain impact on the efficiency of image recognition.