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Home/ Questions/Q 8893471
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Editorial Team
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Editorial Team
Asked: June 14, 20262026-06-14T23:15:23+00:00 2026-06-14T23:15:23+00:00

I need to find the position of a smaller image inside a bigger image.

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I need to find the position of a smaller image inside a bigger image. The smaller image is a subset of the bigger image. The requirement is also that pixel values can slightly differ for example if images were produced by different JPEG compressions.
I’ve implemented the solution by comparing bytes using the CPU but I’m now looking into any possibility to speed up the process.
Could I somehow utilize OpenGLES and thus iPhone GPU for it?

Note: images are grayscale.

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  1. Editorial Team
    Editorial Team
    2026-06-14T23:15:24+00:00Added an answer on June 14, 2026 at 11:15 pm

    @Ivan, this is a pretty standard problem in video compression (finding position of current macroblock in previous frame). You can use a metric for difference in pixels such as sum of abs differences (SAD), sum of squared differences (SSD), or sum of Hadamard-transformed differences (SATD). I assume you are not trying to compress video but rather looking for something like a watermark. In many cases, you can use a gradient descent type search to find a local minimum (best match), on the empirical observation that comparing an image (your small image) to a slightly offset version of same (a match the position of which hasn’t been found exactly) produces a closer metric than comparing to a random part of another image. So you can start by sampling the space of all possible offsets/positions (motion vectors in video encoding) rather coarsely, and then do local optimization around the best result. The local optimization works by comparing a match to some number of neighboring matches, and moving to the best of those if any is better than your current match, repeat. This is very much faster than brute force (checking every possible position), but it may not work in all cases (it is dependent on the nature of what is being matched). Unfortunately, this type of algorithm does not translate very well to GPU, because each step depends on previous steps. It may still be worth it; if you check eg 16 neighbors to the position for a 256×256 image, that is enough parallel computation to send to GPU, and yes it absolutely can be done in OpenGL-ES. However the answer to all that really depends on whether you’re doing brute force or local minimization type search, and whether local minimization would work for you.

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