The key area's I'm interesting in are readability, maintainability, DRY, and if the program performance/efficiency could be imporved in any way.

image scanning class:

score calculation class:

outputs:

special note: this program is designed to work with pixels with 3 channels each (RGB), this is just a dummy example but it also works for fully built out 'images'.

Edit:

Template matching is taking a small 'image' and scanning it over a larger image one pixel at a time until a match is found.

During each iteration of the scan the template and a block of the image, which is the same size as the template, are compared. They are given a score. The closer the score (in this specific scoring metric) to 0 the better. A perfect match gets a score of 0.

The key area's I'm interesting in are readability, maintainability, DRY, and if the program performance/efficiency could be improved in any way.

Image scanning class:

Score calculation class:

Outputs:

Template matching is taking a small 'image' and scanning it over a larger image one pixel at a time until a match is found.

During each iteration of the scan the template and a block of the image, which is the same size as the template, are compared. They are given a score. The closer the score (in this specific scoring metric) to 0 the better. A perfect match gets a score of 0.

Special note:

This program is designed to work with pixels with 3 channels each (RGB), this is just a dummy example but it also works for fully built out 'images'.

Edit:

Template matching is taking a small 'image' and scanning it over a larger image one pixel at a time until a match is found.

During each iteration of the scan the template and a block of the image, which is the same size as the template, are compared. They are given a score. The closer the score (in this specific scoring metric) to 0 the better. A perfect match gets a score of 0.