A Novel Efficient Approach for Screen Image Classification in Remote Display Protocol

In remote display protocols, screen image compression plays an important role to improve quality of experience (QoE) of users and reduce the bandwidth consumption. Not all image elements on the display have the same type, so it is wise to apply a screen image classification for compression decision. In this paper, we propose a novel efficient approach for screen image classification that separate the captured screen into 2 types of blocks: text and non-text block. Our method is a 2-stage process that is different from other works because of the appearance of text localization in the screen image as the first stage. This text localization is mainly based on edge feature and morphological operation in which we experiment with many kinds of edge detection methods. Then block-based classification categorizes the screen image blocks based on the positions of the detected text regions. The experimental results of high accuracy rate and low time consumption state our method is efficient in remote display protocol.