Page Classification for Print Imaging Pipeline
This work addresses the need for more precise image classification in digital copiers and printers to enhance copying or printing quality, but it is incremental as it builds on a previous method.
The paper tackled the problem of improving print quality by extending an existing SVM-based classification method to distinguish five image types (text, picture, mixed, receipt, highlight) instead of three, using four new features.
Digital copiers and printers are widely used nowadays. One of the most important things people care about is copying or printing quality. In order to improve it, we previously came up with an SVM-based classification method to classify images with only text, only pictures or a mixture of both based on the fact that modern copiers and printers are equipped with processing pipelines designed specifically for different kinds of images. However, in some other applications, we need to distinguish more than three classes. In this paper, we develop a more advanced SVM-based classification method using four more new features to classify 5 types of images which are text, picture, mixed, receipt and highlight.