7. A computer-implemented method comprising: binarizing a first image frame to generate a second binarized image frame; outputting the second binarized image frame; receiving a first indication indicating that the second binarized image frame contains at least one of: no text, text that is not recognizable, text that is partially recognizable, or text that is recognizable; determining a first feature metric characterizing image sharpness; generating, using the first feature metric, a first feature value associated with the first image frame; training an image classifier to select an input image frame for optical character recognition using at least the first feature metric and the first indication; receiving an order of sharpness indicating that a third image frame is sharper than a fourth image frame and the fourth image frame is sharper than a fifth image frame; generating, using the first feature metric, a second feature value associated with the third image frame; generating, using the first feature metric, a third feature value associated with the fourth image frame; generating, using the first feature metric, a fourth feature value associated with the fifth image frame; receiving a first score output by the image classifier based on the second feature value; receiving a second score output by the image classifier, based on the third feature value; receiving a third score output by the image classifier, based on the fourth feature value; determining a first correlation between the order of sharpness and the first score, the second score and the third score output by the image classifier; determining that the first correlation satisfies a selection criteria; and selecting the first feature metric for use in image frame selection.
7. A computer-implemented method comprising: binarizing a first image frame to generate a second binarized image frame; outputting the second binarized image frame; receiving a first indication indicating that the second binarized image frame contains at least one of: no text, text that is not recognizable, text that is partially recognizable, or text that is recognizable; determining a first feature metric characterizing image sharpness; generating, using the first feature metric, a first feature value associated with the first image frame; training an image classifier to select an input image frame for optical character recognition using at least the first feature metric and the first indication; receiving an order of sharpness indicating that a third image frame is sharper than a fourth image frame and the fourth image frame is sharper than a fifth image frame; generating, using the first feature metric, a second feature value associated with the third image frame; generating, using the first feature metric, a third feature value associated with the fourth image frame; generating, using the first feature metric, a fourth feature value associated with the fifth image frame; receiving a first score output by the image classifier based on the second feature value; receiving a second score output by the image classifier, based on the third feature value; receiving a third score output by the image classifier, based on the fourth feature value; determining a first correlation between the order of sharpness and the first score, the second score and the third score output by the image classifier; determining that the first correlation satisfies a selection criteria; and selecting the first feature metric for use in image frame selection. 11. The computer-implemented method of claim 7 , further comprising: generating, using a second feature metric, a fifth feature value associated with the third image frame; generating, using the second feature metric, a sixth feature value associated with the fourth image frame; generating, using the second feature metric, a seventh feature value associated with the fifth image frame; receiving a fourth score output by the image classifier based on the fifth feature value; receiving a fifth score output by the image classifier, the fifth score based on the sixth feature value; receiving a sixth score output by the image classifier, the sixth score based on the seventh feature value; determining a second correlation between the order of sharpness and the fourth score, the fifth score and the sixth score output by the image classifier; determining that the second correlation does not satisfy the selection criteria; and retraining the image classifier using a plurality of feature metrics and the first indication, wherein the plurality of feature metrics comprises the first feature metric but omits the second feature metric.