In this paper, a novel approach for detection of text and non-text regions in video frames is proposed. The proposed approach performs block wise eigen analysis on the gradient image of the video frame. For each block of the gradient frame, the dominant eigen value is computed to decide if the block could be a candidate text block. The K-means clustering is then applied to further identify text blocks among the candidate blocks. From each of the identified candidate text blocks edges are extracted using the sobel operator, and then by the use of horizontal and vertical profiles a bounding rectangle is fixed up. Further, geometric properties of the identified text regions are studied to eliminate false text regions. In order to validate the efficacy of the proposed approach, experimentation on a dataset containing 800 video frames has been carried out. The obtained results ensure that the proposed approach is with increased text detection rate with very low false and misdetection rates when compared to the other existing state of the art techniques.