Algorithm to detect overlapping rows of two images

Question

Let\'s say I have 2 images A and B as below.

Notice that the bottom of

Answer 1

Something like this will probably help:

First, traverse the image A from bottom upwards, search for a row with significant information in it. An "information" can be calculated, for example, by counting the total color shift across the row. Say, two adjacent pixels have colors #ffffff and #ff0000 - add 2.0 to total count. Have a series of thresholds ready, and lock on the first row that's reaching that threshold. The series can be "10.0, 0.1*row length, 0.15*row length, ..." to a reasonable limit. Then, traverse this array from topmost discovered downwards, take the corresponding row and search for its match in B from upside down. If found, and the threshold is big enough, take the next one in the array and calculate the position of its match, and compare. If succeed, you have locked a correct offset of B over A, and it equals height_of_A - first_row_index + first_row_match_index. If failed continue searching for the next row. If all matches failed, search for very last row of A from the very first row of B, up to the offset of the first row found from the bottom of A. If again failed, then the answer is 0. Of course, if using JPEG images, use threshold-match, as pixels might not be exact in A and B, perhaps with a tolerance to unmatched pixels as well.