METHODS AND APPARATUS FOR TEXT DETECTION

1 . A method having scanned intensity information as input for detecting text in a scanned page by observing a very strong contrast in a localized region between a dark side and a light side, the method comprising:

determining a stroke width;

contrast-based text detection processing;

wherein the localized region comprises a substantially sharp edge between the dark side and the light side; and

whereby any of black text on white background, black text on color background, and white or light text on a dark background are detected.

2 . The method of claim 1 , further comprising measuring a color saturation value and using the value to improve detection accuracy, wherein the color saturation value of the dark side is required to be small.

3 . The method of claim 2 , further comprising preliminarily single pixel processing to estimate the color saturation value using prior color information provided by the scanner.

4 . The method of claim 1 , furthering comprising detecting the presence of half-tone pixels by using a local indicator to improve detection accuracy.

5 . The method of claim 4 , wherein the half-tone detection is obtained through an algorithm for half-tone detection.

6 . The method of claim 1 , wherein the pre-processing further comprises:

detecting a local ramp; and

identifying an intensity trough.

7 . The method of claim 1 , wherein the contrast-based text detection processing further comprises:

detecting text preliminarily based on local contrast and stroke width; and

consistency checking.

8 . The method of claim 1 , wherein the observing a strong contrast further comprises:

detecting text preliminarily based on local contrast; and

consistency checking.

9 . The method of claim 6 , further comprising:

detecting a local ramp;

identifying an intensity trough;

detecting text preliminarily based on contrast and stroke width; and

consistency checking.

10 . The method of claim 6 , wherein identifying an intensity trough uses a finite state machine algorithm, the algorithm having a sweeping procedure.

11 . The method of claim 6 , wherein the stroke width determination step further comprises:

determining a width and a skeleton, wherein the width is a distance value and the skeleton is a skeletal line; and

detecting closely touching text strokes.

12 . The method of claim 11 , wherein the width and skeleton determining step further comprises:

setting the width value to the smaller of a vertical distance and a horizontal distance between two edges of the stroke; and

determining the skeletal line as a roughly equidistant line from the edges.

13 . The method of claim 11 , wherein the detecting closely touching text strokes further comprises detecting a pattern of dark-light-dark (DLD) in a horizontal or a vertical direction within a very small window.

14 . The method of claim 7 , wherein the detecting text further comprises deciding whether a current pixel is a text pixel by using the local contrast present in an N×N window having a center over a set of pixels and centered at the current pixel, and stroke width at the current pixel.

15 . The method of claim 14 , wherein N=9.

16 . The method of claim 14 , wherein numerous statistics of the pixels within the N×N window are collected by using a set of thresholds.

17 . The method of claim 16 , wherein

the set of thresholds comprises any of:

a first minimum intensity level for text background;

a maximum intensity level of text to be detected;

a second minimum intensity level for text background around crowded text strokes, wherein the second minimum intensity level is smaller than the first minimum intensity level;

a medium threshold value, wherein the medium threshold value is around 50% intensity;

a first maximum width of a stroke, wherein the first width is considered thin; and

a second maximum width of a stroke, wherein the second width is considered very thin; and

wherein the numerous statistics comprise any of:

a number of pixels that are thin;

a number of pixels in the center of a 3×3 window that are thin;

a number of pixels on a skeleton, wherein the skeleton pixels are very thin;

a minimum width among pixels of the center 3×3 pixels;

a second smallest width among the pixels of the center 3×3 pixels, wherein the second smallest width is equal to the minimum width among pixels of the center 3×3 pixels if more than 1 pixel has the minimum width;

a highest intensity present in the N×N window;

a number of light pixels;

a number of non-light pixels;

a number of non-light pixels detected as half-toned from a half-tone detection module;

a number of dark and neutral pixels;

a number of dark and colored pixels;

a number of colored pixels with medium intensity;

a number of dark and neutral pixels after boosting;

a number of pixels in the center 3×3 window, wherein the pixels are dark to medium in intensity;

a thin flag set to 1 if the stroke is thin, or set to zero otherwise; and

a background flag set to 1 if the center 3×3 pixels are all light, or set to zero otherwise.

18 . The method of claim 16 , further comprising determining if the current pixel is in a category of a set of predetermined categories using an associated algorithm and the set of thresholds, wherein the thresholds are chosen empirically.

19 . The method of claim 18 , wherein the predetermined set of categories comprises:

Text Outline;

Text Body;

Background; and

Non-text.

20 . The method of claim 18 , further comprising moving the center of the N×N window by J pixels to obtain a subsampled text tag.

21 . The method of claim 20 , wherein J=3.

22 . The method of claim 7 , wherein the consistency checking further comprises:

accumulating a set of statistics using an N×N window of text tags and a set of thresholds; and

deciding by using the set of statistics if each of the text tags is any of:

Text Outline;

Text Body;

Background; and

Non-text.

23 . The method of claim 22 , wherein the N×N window further comprises N×N blocks, each block representing J×J pixels.

24 . The method of claim 23 , wherein N=5 and J=3.

25 . The method of claim 22 , wherein set the of thresholds comprises a maximum number of Non-text blocks threshold.

26 . An apparatus for receiving scanned intensity information as input for detecting text in a scanned page by observing a very strong contrast in a localized region between a dark side and a light side, the apparatus comprising:

a module for pre-processing for stroke width determination; and

a module for contrast-based text detection processing;

wherein the localized region comprises a substantially sharp edge between the dark side and the light side; and

whereby any of black text on white background, black text on color background, and white or light text on a dark background are detected.