A text region location method based on connected component

Text region location is important to text recognition and retrieval in images of complex background. The existing methods with precision and recall rate have high computational complexity. These methods are unpractical real environment. A text region location method is proposed based on component filtering and K-means clustering. Firstly, the input image is segmented into three layers by an adaptive image segmentation method, and the components are extracted from the character layers. Then, the features of the component are obtained, and Adaboost classifier is used to filter non-character components. The candidates of character components are grouped into text regions by K-means clustering based on the position and layer of the component. The experimental results demonstrate that the precision and the recall rate of the proposed approach is almost the same that of as the other methods, and the proposed method has lower computational complexity.