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For Brisk, it ignores the keypoint.

//Remove keypoints very close to the border
  size_t ksize = keypoints.size();
  std::vector<int> kscales; // remember the scale per keypoint
  kscales.resize(ksize);
  static const float log2 = 0.693147180559945f;
  static const float lb_scalerange = (float)(log(scalerange_) / (log2));
  std::vector<cv::KeyPoint>::iterator beginning = keypoints.begin();
  std::vector<int>::iterator beginningkscales = kscales.begin();
  static const float basicSize06 = basicSize_ * 0.6f;
  for (size_t k = 0; k < ksize; k++)
  {
    unsigned int scale;
      scale = std::max((int) (scales_ / lb_scalerange * (log(keypoints[k].size / (basicSize06)) / log2) + 0.5), 0);
      // saturate
      if (scale >= scales_)
        scale = scales_ - 1;
      kscales[k] = scale;
    const int border = sizeList_[scale];
    const int border_x = image.cols - border;
    const int border_y = image.rows - border;
    if (RoiPredicate((float)border, (float)border, (float)border_x, (float)border_y, keypoints[k]))
    {
      keypoints.erase(beginning + k);
      kscales.erase(beginningkscales + k);
      if (k == 0)
      {
        beginning = keypoints.begin();
        beginningkscales = kscales.begin();
      }
      ksize--;
      k--;
    }
  }

Also for freak:

 // compute the scale index corresponding to the keypoint size and remove keypoints close to the border
    if( scaleNormalized ) {
        for( size_t k = keypoints.size(); k--; ) {
            //Is k non-zero? If so, decrement it and continue"
            kpScaleIdx[k] = max( (int)(log(keypoints[k].size/FREAK_SMALLEST_KP_SIZE)*sizeCst+0.5) ,0);
            if( kpScaleIdx[k] >= FREAK_NB_SCALES )
                kpScaleIdx[k] = FREAK_NB_SCALES-1;

            if( keypoints[k].pt.x <= patternSizes[kpScaleIdx[k]] || //check if the description at this specific position and scale fits inside the image
                 keypoints[k].pt.y <= patternSizes[kpScaleIdx[k]] ||
                 keypoints[k].pt.x >= image.cols-patternSizes[kpScaleIdx[k]] ||
                 keypoints[k].pt.y >= image.rows-patternSizes[kpScaleIdx[k]]
               ) {
                keypoints.erase(kpBegin+k);
                kpScaleIdx.erase(ScaleIdxBegin+k);
            }
        }
    }

Also for Brief:

    //Remove keypoints very close to the border

KeyPointsFilter::runByImageBorder(keypoints, image.size(), PATCH_SIZE/2 + KERNEL_SIZE/2);


void KeyPointsFilter::runByImageBorder( vector<KeyPoint>& keypoints, Size imageSize, int borderSize )
{

    if( borderSize > 0)
    {
        if (imageSize.height <= borderSize * 2 || imageSize.width <= borderSize * 2)
            keypoints.clear();
        else
            keypoints.erase( std::remove_if(keypoints.begin(), keypoints.end(),
                                       RoiPredicate(Rect(Point(borderSize, borderSize),
                                                         Point(imageSize.width - borderSize, imageSize.height - borderSize)))),
                             keypoints.end() );
    }
}

Not what exactly is edgeThreshold in Orb, but is seems to ignore the keypoints:

 // Remove keypoints very close tothe borderKeyPointsFilter::runByImageBorder(keypoints, imagePyramid[level].size(), edgeThreshold);

For Brisk, it ignores the keypoint.

//Remove keypoints very close to the border
  size_t ksize = keypoints.size();
  std::vector<int> kscales; // remember the scale per keypoint
  kscales.resize(ksize);
  static const float log2 = 0.693147180559945f;
  static const float lb_scalerange = (float)(log(scalerange_) / (log2));
  std::vector<cv::KeyPoint>::iterator beginning = keypoints.begin();
  std::vector<int>::iterator beginningkscales = kscales.begin();
  static const float basicSize06 = basicSize_ * 0.6f;
  for (size_t k = 0; k < ksize; k++)
  {
    unsigned int scale;
      scale = std::max((int) (scales_ / lb_scalerange * (log(keypoints[k].size / (basicSize06)) / log2) + 0.5), 0);
      // saturate
      if (scale >= scales_)
        scale = scales_ - 1;
      kscales[k] = scale;
    const int border = sizeList_[scale];
    const int border_x = image.cols - border;
    const int border_y = image.rows - border;
    if (RoiPredicate((float)border, (float)border, (float)border_x, (float)border_y, keypoints[k]))
    {
      keypoints.erase(beginning + k);
      kscales.erase(beginningkscales + k);
      if (k == 0)
      {
        beginning = keypoints.begin();
        beginningkscales = kscales.begin();
      }
      ksize--;
      k--;
    }
  }

Also for freak:

 // compute the scale index corresponding to the keypoint size and remove keypoints close to the border
    if( scaleNormalized ) {
        for( size_t k = keypoints.size(); k--; ) {
            //Is k non-zero? If so, decrement it and continue"
            kpScaleIdx[k] = max( (int)(log(keypoints[k].size/FREAK_SMALLEST_KP_SIZE)*sizeCst+0.5) ,0);
            if( kpScaleIdx[k] >= FREAK_NB_SCALES )
                kpScaleIdx[k] = FREAK_NB_SCALES-1;

            if( keypoints[k].pt.x <= patternSizes[kpScaleIdx[k]] || //check if the description at this specific position and scale fits inside the image
                 keypoints[k].pt.y <= patternSizes[kpScaleIdx[k]] ||
                 keypoints[k].pt.x >= image.cols-patternSizes[kpScaleIdx[k]] ||
                 keypoints[k].pt.y >= image.rows-patternSizes[kpScaleIdx[k]]
               ) {
                keypoints.erase(kpBegin+k);
                kpScaleIdx.erase(ScaleIdxBegin+k);
            }
        }
    }

Also for Brief:

    //Remove keypoints very close to the border

KeyPointsFilter::runByImageBorder(keypoints, image.size(), PATCH_SIZE/2 + KERNEL_SIZE/2);


void KeyPointsFilter::runByImageBorder( vector<KeyPoint>& keypoints, Size imageSize, int borderSize )
{

    if( borderSize > 0)
    {
        if (imageSize.height <= borderSize * 2 || imageSize.width <= borderSize * 2)
            keypoints.clear();
        else
            keypoints.erase( std::remove_if(keypoints.begin(), keypoints.end(),
                                       RoiPredicate(Rect(Point(borderSize, borderSize),
                                                         Point(imageSize.width - borderSize, imageSize.height - borderSize)))),
                             keypoints.end() );
    }
}

Not what exactly is edgeThreshold in Orb, but is seems to ignore the keypoints:

 // Remove keypoints very close tothe borderKeyPointsFilter::runByImageBorder(keypoints, border
KeyPointsFilter::runByImageBorder(keypoints, imagePyramid[level].size(), edgeThreshold);