Color cast image recognition method

Abstract

The invention provides a color cast image recognition method. A neural network model is used to recognize whether an input image is a color cast image or not, and a training set used for training theneural network model is constructed by using a normal image set and a color cast image set generated on the basis of the normal image set. Based on the method of generating the color cast image set onthe basis of the normal image set, the problem of a data set for classifying the color cast images can be effectively solved, and the color cast images can be effectively recognized.

Description

technical field [0001] The invention relates to a color shift image recognition method. Background technique [0002] The convolutional neural network imitates the structure of the human cerebral cortex, processes the input data in layers, and then superimposes them layer by layer to mine the hidden features and laws in the data to achieve the purpose of distinction and recognition. In the process of hierarchical processing of data, the first few layers of processing extract shallow features such as image contour color, while the latter layer focuses on extracting more abstract features. Each layer includes a number of neurons, as the basic unit of data processing. The more layers and the more neurons in each layer, the greater the amount of information carried by the deep learning network and the stronger the processing function. In the process of superimposing the data, the extracted features are superimposed together, and then related functions such as softmax are appli...

AI Technical Summary

Problems solved by technology

However, there is currently no image training set and test set for color cast image discrimination, making further machine learning work impossible

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