Added harfbuzz; use it instead of STB to render text #29300
Merge with https://github.com/opencv/opencv_extra/pull/1378.
This is the next big step to improve font rendering in OpenCV 5.x. See #18760, #26301. See also OpenCV 5.0 release notes, where it was pointed out that complex scripts are not rendered correctly, and HarfBuzz integration is needed to fix it. So, here it is — HarfBuzz integration:
* Removed tweaked STB engine. STB truetype rendering engine was included into OpenCV 5.0-pre/5.0 and it was extended to instantiate and render variable fonts, but the support was incomplete and immature.
* Instead, we now use [HarfBuzz](https://github.com/harfbuzz/harfbuzz) — famous font shaping library and now also font rendering library, used by many big companies and organizations.
* As a result, we now correctly render complex scripts, such as arabic or devanagari, correctly handle font ligatures (ff, fi, ft etc.)
<img width="1300" height="600" alt="text_test" src="https://github.com/user-attachments/assets/a7d2c754-0fcf-40f8-8104-578f3a14850b" />
* Potentially, we could also support color emoji, but that would be a next step.
* As with STB-based engine, glyphs are cached (the same glyph from the same font is not rendered twice), so the performance should be on par with the previous engine.
* When OpenCV is built with `-DWITH_HARFBUZZ=ON`, which is set by default, it tries to detect HarfBuzz in the system and use it. If it's not detected, OpenCV builds our own small subset of HarfBuzz.
The following table compares size of libopencv_imgproc.dylib.5.0.0 (Release mode) in different configurations:
| Configuration | libopencv_imgproc (stripped) | delta vs 5.0 |
|----------------------------------------|------------------------------|----------|
| imgproc without text rendering (`-DWITH_HARFBUZZ=OFF`) | 4.27 MB | −2.35 MB |
| imgproc with stb-based engine (5.0) | 6.62 MB | 0.0 Mb |
| imgproc with HarfBuzz-based engine (this PR) | 7.07 MB | +0.45 MB |
The biggest source of the size increase when OpenCV is built with text rendering support (STB- or Harfbuzz-based) is that imgproc in this case includes .ttf fonts (Rubik and 'Wen Quan Yi Micro Hei'), which are gzip-compressed, but still have noticeable size, especially 'Wen Quan Yi' (~2Mb). HarfBuzz itself, compared to STB engine, adds just 0.45Mb, or ~7% to imgproc size. On other platforms (Linux x64, Windows), where IPP or other acceleration libraries are linked into libopencv_imgproc, the harfbuzz footprint is even less noticeable.
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imgproc: fix INTER_NEAREST_EXACT to match Pillow (5.x retarget of #28661) #28873
## Summary
Fixes `INTER_NEAREST_EXACT` producing different results from Pillow for images with dimensions that are multiples of 64 (e.g., 128, 192).
Retargets #28661 to 5.x per core team request.
## Root cause
The old 16-bit fixed-point arithmetic (`ifx`, `ifx0`, `>> 16`) rounds differently from Pillow's pixel-center coordinate mapping. At exact pixel boundaries (e.g., y=7 with 128 to 160: `0.4 + 7*0.8 = 5.999999999999999`), Pillow's truncation drops to 5 while the old opencv formula rounds to 6.
## Changes
- `resize.cpp`: Replace `ifx/ifx0/ify/ify0` 16-bit fixed-point with an int64 arithmetic formula equivalent to `floor((i + 0.5) * src / dst)`, computed as `((int64_t)(i * 2 + 1) * src) / (dst * 2)`. This matches Pillow's pixel-center mapping exactly, is deterministic across platforms, and avoids FP rounding divergence entirely.
- `test_resize_bitexact.cpp`: Add `NearestExact_PillowCompat` covering 4 dimension pairs including the reproducer from #28429.
## Testing
- All 3 `Resize_Bitexact` tests pass (Linear8U, Nearest8U, NearestExact_PillowCompat) on this branch built against 5.x
- Verified bit-exact match to PIL output (Python 3.14, Pillow) on 49 dimension combinations including random pairs
- Built on macOS ARM64 with HAL (carotene/KleidiCV) active
Fixes#28429
Inverted imgproc-geometry dependency and moved more functions to geometry #29230
Fixes: https://github.com/opencv/opencv/issues/20267
Continues: https://github.com/opencv/opencv/pull/29175
OpenCV Contrib: https://github.com/opencv/opencv_contrib/pull/4137
OpenCV Extra: https://github.com/opencv/opencv_extra/pull/1377
Summary:
- LSD returned back to imgproc
- drawing functions moved to imgproc
- undistort image and related perf-pixel functions moved to imgproc
- moments moved to geometry
- estimateXXXtransform moved to geometry
After the patch the geometry module depends on code and Flann and may be used everywhere without potential circular dependencies
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Revised bicubic interpolation kernels and updated the corresponding functions #29165
They should work more accurately and faster than the existing implementation. The PR follows the previous work (#26271 etc.) that brought faster bilinear kernels.
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Moved geometry transformations from imgproc to 3d, future geometry module #29101
The first step of 2d geometry operations migration to the future geometry module.
I created 2d.hpp to isolate the moved functions for now. I propose to create geometry.hpp when the module is renamed and include all things there.
OpenCV contrib: https://github.com/opencv/opencv_contrib/pull/4126
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imgproc: add findTRUContours - lock-free parallel contour extraction #28773
Integrates the TRUCO algorithm (Threaded Raster Unrestricted Contour Ownership, @cite TRUCO2026) as a transparent fast path inside `cv::findContours`. No API change is required: existing code automatically benefits when `mode=RETR_LIST` and no hierarchy output is requested.
### How it works
When `mode=RETR_LIST` and the caller does not request hierarchy, `findContours` delegates to the TRUCO parallel engine instead of Suzuki-Abe. All ContourApproximationModes are supported; approximation is applied in parallel after extraction. In all other cases the original Suzuki-Abe path is used unchanged.
### Key design ideas
- Row-strip domain decomposition parallelised via `cv::parallel_for_`
- Start-point ownership rule + speculative downward tracing eliminate tile stitching and synchronisation primitives (lock-free)
- 8-bit state space instead of the 32-bit integer labeling required by Suzuki-Abe, giving higher SIMD throughput and lower memory-bandwidth pressure
- Paged contour buffer (`TRUCOPagedContour`) avoids heap reallocation on the hot tracing path
- SIMD-accelerated row scanning via `cv::v_uint8` intrinsics
- Thread count controlled globally via `cv::setNumThreads()`, consistent with OpenCV conventions
### Output correctness
Significant effort has gone into ensuring the output is identical to the original `findContours` in every respect: same contour set, same ordering, and same approximation results for all methods. A dedicated test suite (`test_contours_truco.cpp`) verifies exact match against Suzuki-Abe across all four `ContourApproximationModes` and thread counts from 1 to 39, using noise images, circles, nested rectangles, and mixed scenes.
### Performance vs. Suzuki-Abe (from submitted paper)
- single-thread: ~1.8–1.9× faster (8-bit SIMD advantage)
- 20 threads: ~14–20× faster on i7-13700H (6P+8E, 20T)
- 20 threads: ~10–12× faster on Xeon Silver 4510 (12C/24T)
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fix: Guard ndsrvp filter center copy when source span is empty #28915
## Summary
This adds a defensive guard around the centre-region `memcpy` in the ndsrvp HAL filter padding path.
**Description**: Multiple memcpy calls in the ndsrvp HAL filter, bilateral filter, and median blur routines use computed sizes (e.g., cnes * (rborder - j), cn * (rborder - j), src_step * height) without validating that the computed byte count fits within the destination buffer. An attacker supplying a crafted image with manipulated dimensions, channel counts, or border parameters can cause the computed copy size to exceed the allocated destination buffer, resulting in a heap buffer overflow that corrupts adjacent memory.
## Changes
- `hal/ndsrvp/src/filter.cpp`
## Verification
- [x] Build passes
- [x] Scanner re-scan confirms fix
- [x] LLM code review passed
---
*Automated security fix by [OrbisAI Security](https://orbisappsec.com)*
fitEllipseDirect: replace det(M) threshold with eigenvector quality check
- Add Ts ≈ 0 guard to avoid division by zero in Schur complement
- Move eigenNonSymmetric inside perturbation loop
- Validate eigenvector with 4ac-b² > 1e-6*||v||² to filter garbage from
complex eigenvalues
fitEllipseAMS: scale threshold by 1/n^5 to match det(M) magnitude
Add Imgproc_FitEllipseDirect_NearCircular regression test
Fix IPP warpAffine #28562
The issue is that we compute the inverse transformation and pass that to the HAL, but tell IPP that we use the actual transformation.
https://github.com/opencv/opencv/blob/a269a489b94b84717691533a04f79d9a0e5f479a/modules/imgproc/src/imgwarp.cpp#L2399-L2412
I have added an additional test with `CV_16S` Mats to test the IPP implementation, because right now no other `warpAffine` test enters the IPP branch.
This fixes#28554.
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Fix integer overflow in medianBlur #28386
The bug in #28385 is that the pointer arithmetic in
https://github.com/opencv/opencv/blob/d8bc5b94b851d5b392c61e5b954fba992e18bb73/modules/imgproc/src/median_blur.simd.hpp#L666-L668
overflows if `i*sstep` is larger than `INT_MAX`, because both variables are of type `int`. If one operand is of type `size_t` instead, the other operand gets promoted to `size_t` before multiplication and overflow doesn't happen anymore.
The test allocates 2.3GB for the Mat; I hope that's okay.
This PR fixes#28385
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docs(imgproc): clarify cv::moments behavior for degenerate contours #28227
relates to https://github.com/opencv/opencv/issues/28222
Clarifies that for degenerate contours (single point or collinear points),
cv::moments() returns m00 == 0 and centroid is undefined.
Documents common workarounds such as boundingRect center or point averaging.
Fix the out-of-bounds read in cv::bilateralFilter for 32f images #28259
### Root Cause Analysis
The issue was caused by a discrepancy between the image range used to allocate the color weight look-up table (LUT) and the actual range of pixel values encountered during filtering, especially near the image borders.
- Range Computation: `cv::bilateralFilter` computes the min/max values of the source image and allocates a `LUT (expLUT)` of size `kExpNumBins + 2` based on this range.
- Border Padding: If `cv::BORDER_CONSTANT` is used (defaulting to 0), and 0 is outside the image's original range (e.g., an image with values between 100 and 200), the padded image will contain values (0) that create differences larger than those accounted for in the `LUT`.
- Out-of-Bounds Access: When calculating the color weight, the code computes an index `idx` from the absolute difference. If this difference exceeds the expected range, `idx` can reach or exceed `kExpNumBins + 1`. Since the code performs linear interpolation using `expLUT[idx]` and `expLUT[idx + 1]`, an `idx` of `kExpNumBins + 1` causes an access to `expLUT[kExpNumBins + 2]`, which is out of bounds.
### Fix
I implemented a robust clamping mechanism in both the SIMD (AVX/SSE) and scalar paths of the bilateral filter invoker:
- Signature Update: Updated `bilateralFilterInvoker_32f` to accept `kExpNumBins` (the maximum valid `LUT` index).
- Clamping: Clamped the computed color difference (alpha) to `kExpNumBins` before calculating the `LUT` index. This ensures that any difference exceeding the planned range is safely treated as the maximum difference in the `LUT` (which usually corresponds to a weight of 0), avoiding any out-of-bounds memory access.
### Modified Files
Modified Files:
`modules/imgproc/src/bilateral_filter.simd.hpp`: Updated the invoker class and SIMD/scalar loops to clamp the LUT index.
`modules/imgproc/src/bilateral_filter.dispatch.cpp`: Updated the dispatch call site to pass the correct LUT size.
Closes#28254
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imgproc: fix heap-buffer-overflow in stackBlur #28233#28250
### Summary
Fixes a heap-buffer-overflow in `cv::stackBlur` when the kernel size is larger than the image dimensions
### Changes
* Added input validation to clamp the kernel size to the image dimensions.
* Added a regression test (`regression_28233`) covering 1x1 and small image cases.
Fixes#28233
Keep convexHull output indices monotone if possible #28163
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/24907 ?
resolves https://github.com/opencv/opencv/issues/4954
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Fixed issues identified by PVS Studio #28185
Partially fixes https://github.com/opencv/opencv/issues/28167
Paper: https://pvs-studio.com/en/blog/posts/cpp/1321/
Closed items: N2, N4, N5, N6, N7, N8, N10, N11, N13, N14.
To be continued...
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Iterative Phase Correlation #28146
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Test: Add regression test for LINE_4 vs LINE_8 connectivity #28120
Add test to verify correct behavior of LINE_4 (4-connected) and LINE_8 (8-connected) line drawing. This test ensures:
- LINE_4 produces staircase pattern (more pixels) for diagonal lines
- LINE_8 produces diagonal steps (fewer pixels)
- LINE_4 pixels have only horizontal/vertical neighbors (no diagonal-only)
Regression test for issue #26413 where LINE_4 and LINE_8 behaviors were swapped.
Correct minAreaRect angle to be in range [-90, 0) #28051
### Pull Request Readiness Checklist
Box angle range over all imgproc tests is in interval `[-90, -0.0581199]`
resolves https://github.com/opencv/opencv/issues/27667
resolves https://github.com/opencv/opencv/issues/19472
resolves https://github.com/opencv/opencv/issues/24436
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Handle near-zero convexity in convexHull #28043
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/21482
closes https://github.com/opencv/opencv/issues/14401
Also skip a code that determines orientation inside rotatingCalipers and rely on the order after convexHull
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Fixed standard HoughLines output shift for rho. #27992
Closes: https://github.com/opencv/opencv/issues/25038
Replaces: https://github.com/opencv/opencv/pull/25043
Merge with https://github.com/opencv/opencv_extra/pull/1288
The original implementation introduces systematic shift (-rho/2) for odd indexes. Integer division just gives proper rounding.
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Try to fix distant points to save time when ThickLine() calls FillConvexPoly() #27366
Proposal for #27365
cv::clipLine() is useful, but one should take care of a margin to preserve line caps.
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Vadim Pisarevsky
Matt Van Horn
Alexander Smorkalov
Alexander Smorkalov
Vincent Rabaud
Maksim Shabunin
Rafael Muñoz Salinas
orbisai0security
Ismail
gideok Kim
Adrian Kretz
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