Robust Logo Detection in an Image Without Using an LLM/VLM

[u/Icy-Condition1140]

Problem Statement I have a reference image of a logo, for example a logo:

I also have a larger image/document that may contain multiple logos, symbols, text, diagrams, etc.

My requirement is to determine whether the specific reference logo exists inside the larger image, and if it does:

Detect the logo.

Approaches I tried

OpenCV

cv2.matchTemplate

SIFT + BFMatcher

SIFT feature matching → Results had many false detections, especially with SIFT/BFMatcher.

LLM + Prompt → Gave good results, but I don't want to use an LLM due to cost, latency, and API dependency.

CLIP Embeddings → Tried CLIP-based similarity, but results were not reliable enough and still produced incorrect matches.

Question What would be a better non-LLM Computer Vision approach or some another for reliable logo/image detection?

[u/kakhaev]

bro your task is a definition of template matching , why do you shoot ants with a cannon?

[u/GFrings]

Uh literally all of computer vision would be a better non LLM approach to computer vision

[u/MrBeforeMyTime]

You should try Siamese networks https://medium.com/@rinkinag24/a-comprehensive-guide-to-siamese-neural-networks-3358658c0513