本文整理了Java中org.opencv.imgproc.Imgproc.adaptiveThreshold()方法的一些代码示例，展示了Imgproc.adaptiveThreshold()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Imgproc.adaptiveThreshold()方法的具体详情如下：
包路径：org.opencv.imgproc.Imgproc
类名称：Imgproc
方法名：adaptiveThreshold

Imgproc.adaptiveThreshold介绍

[英]Applies an adaptive threshold to an array.

The function transforms a grayscale image to a binary image according to the formulae:

• THRESH_BINARY

dst(x,y) = maxValue if src(x,y) > T(x,y); 0 otherwise

• THRESH_BINARY_INV

dst(x,y) = 0 if src(x,y) > T(x,y); maxValue otherwise

where T(x,y) is a threshold calculated individually for each pixel.

• For the method ADAPTIVE_THRESH_MEAN_C, the threshold value T(x,y) is a mean of the blockSize x blockSize neighborhood of (x, y) minus C.
• For the method ADAPTIVE_THRESH_GAUSSIAN_C, the threshold value T(x, y) is a weighted sum (cross-correlation with a Gaussian window) of the blockSize x blockSize neighborhood of (x, y) minus C. The default sigma (standard deviation) is used for the specified blockSize. See "getGaussianKernel".

The function can process the image in-place.
[中]将自适应阈值应用于阵列。
该函数根据以下公式将灰度图像转换为二值图像：
THRESH_二进制
如果src（x，y）>T（x，y），则dst（x，y）=最大值；否则为0
阈值二元变量
如果src（x，y）>T（x，y），则dst（x，y）=0；否则为最大值
其中T（x，y）是为每个像素单独计算的阈值。
对于方法ADAPTIVE_THRESH_MEAN_C，阈值T（x，y）是（x，y）的blockSize x blockSize邻域减去C的平均值。
对于方法ADAPTIVE_THRESH_GAUSSIAN_C，阈值T（x，y）是（x，y）的blockSize x blockSize邻域减去[$3$]的加权和（与高斯窗口的互相关）。默认西格玛（标准偏差）用于指定的blockSize。见“getGaussianKernel”。
该功能可以就地处理图像。

代码示例

代码示例来源：origin: openpnp/openpnp

public static Mat thresholdAdaptive(Mat mat, boolean invert) {
  Imgproc.adaptiveThreshold(mat, mat, 255, Imgproc.ADAPTIVE_THRESH_MEAN_C,
      invert ? Imgproc.THRESH_BINARY_INV : Imgproc.THRESH_BINARY, 3, 5);
  return mat;
}

代码示例来源：origin: openpnp/openpnp

public FluentCv thresholdAdaptive(boolean invert, String... tag) {
  Imgproc.adaptiveThreshold(mat, mat, 255, Imgproc.ADAPTIVE_THRESH_MEAN_C,
      invert ? Imgproc.THRESH_BINARY_INV : Imgproc.THRESH_BINARY, 3, 5);
  return store(mat, tag);
}

代码示例来源：origin: hschott/Camdroid

protected void execute() {
  Mat gray = gray();
  Imgproc.adaptiveThreshold(gray, out, 255,
      Imgproc.THRESH_BINARY_INV, Imgproc.ADAPTIVE_THRESH_MEAN_C,
      blocksize, reduction);
}

代码示例来源：origin: JavaOpenCVBook/code

protected void processOperation() {
  if(adaptiveMeanString.equals(thresholdMode)){
    Imgproc.adaptiveThreshold(originalImage, image, maxval, Imgproc.ADAPTIVE_THRESH_MEAN_C, Imgproc.THRESH_BINARY, blockSize, constantC);	
  }
  else if(noneString.equals(thresholdMode)){
    image = originalImage.clone();
  }
  else{
    Imgproc.threshold(originalImage, image, level, maxval, modeMap.get(thresholdMode));
  }
  
  updateView(image);
}

代码示例来源：origin: openpnp/openpnp

@Override
  public Result process(CvPipeline pipeline) throws Exception {
    Mat mat = pipeline.getWorkingImage();
    Imgproc.adaptiveThreshold(mat, mat, 255, adaptiveMethod.getCode(), invert ? Imgproc.THRESH_BINARY_INV : Imgproc.THRESH_BINARY, blockSize, cParm);
    return null;
  }
}

代码示例来源：origin: hschott/Camdroid

protected void execute() {
  out = gray();
  Imgproc.equalizeHist(out, out);
  Core.normalize(out, out, min, max, Core.NORM_MINMAX);
  Imgproc.adaptiveThreshold(out, out, 255, Imgproc.THRESH_BINARY,
      Imgproc.ADAPTIVE_THRESH_MEAN_C, blocksize, reduction);
  byte[] data = new byte[(int) out.total()];
  out.get(0, 0, data);
  this.tessBaseAPI.setImage(data, out.width(), out.height(),
      out.channels(), (int) out.step1());
  String utf8Text = this.tessBaseAPI.getUTF8Text();
  int score = this.tessBaseAPI.meanConfidence();
  this.tessBaseAPI.clear();
  if (score >= SIMPLETEXT_MIN_SCORE && utf8Text.length() > 0) {
    simpleText = utf8Text;
  } else {
    simpleText = new String();
  }
}