Text detection in video frames provide highly condensed information about the content of the video and it is useful for video seeking, browsing, retrieval and understanding video text in large video databases. In this paper, we propose a hybrid method that it automatically detects segments and recognizes the text present in the video. Detection is done by using laplacian method based on wavelet and color features. Segmentation of detected text is divided into two modules Line segmentation and Character segmentation. Line segmentation is done by using mathematical statistical method based on projection profile analysis. In line segmentation, multiple lines of text in video frame obtained from text detection are segmented into single line. Character segmentation is done by using Connected Component. Analysis (CCA) and Vertical Projection Profile Analysis. The input for character segmentation is the line of text obtained from line segmentation, in which all the characters in the line are segmented separately for recognition. Optical character recognition is Processed by using template matching and correlation technique. Template matching is performed by comparing an input character with a set of templates, each comparison results in a similarity measure between the input characters with a set of templates. After all templates have been compared with the observed character image, the character’s identity is assigned with the most similar template based on correlation. Eventually, the text in video frame is detected, segmented, and processed to OCR for recognition.