For improving accuracy

validating text is a key step of detecting text in video.The current approaches mostly based on experiential rules.The approaches are not adaptive

in condition of complex background

low resolution

varied font

size

color of text in video.For improving adaptability and accuracy of validating text

the application of two-dimension principal component analysis(2DPCA) for video frame processing is investigated and a novel 2DPCA and support vector machine(SVM) based approach for validating text in video is proposed.The approach has two steps of training and validating.Firstly

2DPCA is adopted to get the features of video image patches.Then

SVM is trained to validate and classify video image patches.The experimental results illustrate that the novel approach for validating text in video is more effective and costs less time than the other approaches

in condition of complex background

low resolution

varied font

size

color of text in video.