The basic steps of the connected-component text extraction algorithm are given below,

and diagrammed in Figure 10. The details are discussed in the following sections.

1. Convert the input image to YUV color space. The luminance(Y) value is used for

further processing. The output is a gray image.

2. Convert the gray image to an edge image.

3. Compute the horizontal and vertical projection profiles of candidate text regions

using a histogram with an appropriate threshold value.

4. Use geometric properties of text such as width to height ratio of characters to

eliminate possible non-text regions.

5. Binarize the edge image enhancing only the text regions against a plain black

background.

6. Create the Gap Image (as explained in the next section) using the gap-filling

process and use this as a reference to further eliminate non-text regions the

output.

-The basic steps of the connected-component text extraction algorithm are given below,

and diagrammed in Figure 10. The details are discussed in the following sections.

1. Convert the input image to YUV color space. The luminance(Y) value is used for

further processing. The output is a gray image.

2. Convert the gray image to an edge image.

3. Compute the horizontal and vertical projection profiles of candidate text regions

using a histogram with an appropriate threshold value.

4. Use geometric properties of text such as width to height ratio of characters to

eliminate possible non-text regions.

5. Binarize the edge image enhancing only the text regions against a plain black

background.

6. Create the Gap Image (as explained in the next section) using the gap-filling

process and use this as a reference to further eliminate non-text regions　the

output.