A method for preprocessing a region of a video containing text for improving optical character recognition, the method comprising computer implemented steps of: a. locating a text image in the region of the video containing the text in the plurality of frames of the text containing region of video; b. enhancing the text image so located in the region of the video containing the text to a higher resolution by applying a combination of a six tap finite impulse response filter with a plurality of filter coefficients to zoom the region of interest two times in height and width, applying an interpolation technique to further zoom the region of interest two times in height and width, applying a discrete cosine transform on the text image, applying a butterworth low pass filter to discard high frequency components and applying an inverse discrete cosine transform to reconstruct the text image; c. binarizing the enhanced high resolution text image; d. finding the width of each connected component in the binarized text image; e. determining average component width in the binarized text image using μ WC = 1 n ∑ i = 1 WC i, where n is the number of components in the region of interest and WC i is the width of the i th connected component; f. segmenting at least two touching characters of the binarized text image by finding standard deviation σ WC of component width, with the determined average component width in the binarized text image, using σ WC = STDEV ( WC i) and defining threshold of character length in the binarized text image as T WC = μ WC + 3 σ WC; and g. identifying a keyword from the segmented text image as an improved input for optical character recognition. a. locating a text image in the region of the video containing the text in the plurality of frames of the text containing region of video; b. enhancing the text image so located in the region of the video containing the text to a higher resolution by applying a combination of a six tap finite impulse response filter with a plurality of filter coefficients to zoom the region of interest two times in height and width, applying an interpolation technique to further zoom the region of interest two times in height and width, applying a discrete cosine transform on the text image, applying a butterworth low pass filter to discard high frequency components and applying an inverse discrete cosine transform to reconstruct the text image; c. binarizing the enhanced high resolution text image; d. finding the width of each connected component in the binarized text image; e. determining average component width in the binarized text image using μ WC = 1 n ∑ i = 1 WC i, where n is the number of components in the region of interest and WC i is the width of the i th connected component; f. segmenting at least two touching characters of the binarized text image by finding standard deviation σ WC of component width, with the determined average component width in the binarized text image, using σ WC = STDEV ( WC i) and defining threshold of character length in the binarized text image as T WC = μ WC + 3 σ WC; and g. identifying a keyword from the segmented text image as an improved input for optical character recognition.