Task 5 of 5

Payoff: Present or Absent?

Everything so far, pointed at a real question. brightScene hides an 8×8 patch; patch is that patch. rotatedPatch is the same eight by eight values turned a quarter turn — identical mean, identical spread, identical histogram, and nowhere in the scene. Find the one; refuse the other.

The kernel is finished (it is task 4's, unchanged). What is left is the part that catches people twice: reading an answer off a score map.

Take the maximum. NCC is a similarity, so its best is its largest. SSD was a distance, so its best was its smallest. The convention is inverted between the two measures, and reaching for the wrong one does not give you a slightly worse answer — it gives you the map's most emphatically wrong position.

The coordinates are the window's top-left corner. Cell (x, y) scored the window that starts at (x, y) and runs 8 pixels right and down. That corner is the answer. The centre is (x + 4, y + 4) if that is what you want — just be sure you know which one you are reporting, because the score map is 89 wide where the scene is 96, and quietly mixing the two coordinate systems is how a detector ends up drawing boxes in the wrong place.

And then the honest part. A search over 7,921 positions always returns a winner — the best score is a best score whether or not anything is there. What turns matching into detection is a threshold: a line below which "the best I found" means "nothing". Here the patch that is present scores 1.000 and the one that is absent tops out near 0.47, so 0.9 separates them with room to spare. That number is not universal — it depends on the noise, on the template, and on how much deformation you are willing to forgive — and calibrating it against data whose answers you already know is most of the work in building a real detector.

Goal: report where patch is, report that rotatedPatch is not there, and let THRESHOLD be what decides.

Requirements

Score both templates against brightScene with the same kernel
Finish bestMatch: scan for the largest score and return the window's top-left corner
console.log the position found for patch, and the best score each template managed
For each template, console.log whether its best score clears THRESHOLD — one true, one false

Hint 1 — the scan

Start from -Infinity and keep the larger:

let best = -Infinity;
let bx = 0;
let by = 0;
for (let y = 0; y < map.length; y++) {
  for (let x = 0; x < map[y].length; x++) {
    if (map[y][x] > best) {
      best = map[y][x];
      bx = x;
      by = y;
    }
  }
}

bx and by are already the corner — no offset to add.

Hint 2 — the verdict

prepare() hands the kernel what task 4 built, so each report is three lines:

const map = await ncc(brightScene, t.centered, t.norm);
const hit = bestMatch(map);
console.log(label, hit.x, hit.y, hit.score,
  hit.score >= THRESHOLD);

Same idea elsewhere

Thresholding a similarity map is the last mile of nearly every classical detector — Viola-Jones cascades, ORB and SIFT keypoint matching with Lowe's ratio test, stereo correspondence rejecting low-confidence disparities — and it survives into modern ones as the confidence score on every bounding box a neural network emits. The score tells you which position is most like the template; only a threshold tells you whether the template is there at all.

All tasks in Template Matching

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