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Anshu
fe160f3eed
imgproc: fix minEnclosingCircle O(n^3) worst case by adding Welzl shuffle #28548 Welzl's algorithm requires random permutation of input points to achieve expected O(n) time. Without shuffling, sorted inputs such as those produced by findContours() trigger O(n^3) worst case. Fix: copy input to std::vector<PT> and apply cv::randShuffle() before processing. Uses OpenCV's RNG so cv::setRNGSeed() ensures reproducible behavior. Original benchmark (5088 contour points, Release, AVX2): findContours output: 3.93 ms → 0.033 ms (119x speedup) Random points: 0.051 ms → 0.049 ms (no regression) Perf test results (this PR, Release, AVX2): | Input | N | Time | |-------|---|------| | Sequential circle points | 10000 | 0.03 ms | | Sequential circle points | 5000 | 0.01 ms | | Random points (CV_32F) | 100000 | 1.87 ms | | Random points (CV_32S) | 100000 | 2.81 ms | Fixes #28546 ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake