conversion between Mat and BufferedImage

最新推荐文章于 2023-09-12 02:29:35 发布

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最新推荐文章于 2023-09-12 02:29:35 发布

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本文介绍如何在Java中实现OpenCV的Mat结构与Java的BufferedImage之间的相互转换。通过两个核心函数mat2Img和img2Mat，实现了图像数据在不同格式间的无缝切换，便于跨平台和跨库操作。

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Introduction

In this tip, we see how to do the conversion between Mat and BufferedImage. Mat is a data structure from OpenCV to process image. BufferedImage is a data structure from Java to store images.

Using the Code

Convert Mat to BufferedImage

Mat data structure has image data, image type (GRAY, BGR), Height, Width. In mat2Img, the following function extracts meta data from Mat data structure and gets assigned to BufferedImage. This way, Mat is assigned toBufferedImage.

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public static BufferedImage mat2Img(Mat in)
    {
        BufferedImage out;
        byte[] data = new byte[320 * 240 * (int)in.elemSize()];
        int type;
        in.get(0, 0, data);

        if(in.channels() == 1)
            type = BufferedImage.TYPE_BYTE_GRAY;
        else
            type = BufferedImage.TYPE_3BYTE_BGR;

        out = new BufferedImage(320, 240, type);

        out.getRaster().setDataElements(0, 0, 320, 240, data);
        return out;
    }

Convert BufferedImage to Mat

img2Mat function accepts BufferedImage object as parameter and returns the Mat object. Mat Object is created with 320 width and 240 height, then extract RGB values from BufferedImage object and assigned todatabuff which is a one dimensional int array. databuff is right shifted to 16 , 8, 0 gets ANDED with 0XFF, then assigned to Mat object.

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public static Mat img2Mat(BufferedImage in)
    {
          Mat out;
          byte[] data;
          int r, g, b;

          if(in.getType() == BufferedImage.TYPE_INT_RGB)
          {
              out = new Mat(240, 320, CvType.CV_8UC3);
              data = new byte[320 * 240 * (int)out.elemSize()];
              int[] dataBuff = in.getRGB(0, 0, 320, 240, null, 0, 320);
              for(int i = 0; i < dataBuff.length; i++)
              {
                  data[i*3] = (byte) ((dataBuff[i] >> 16) & 0xFF);
                  data[i*3 + 1] = (byte) ((dataBuff[i] >> 8) & 0xFF);
                  data[i*3 + 2] = (byte) ((dataBuff[i] >> 0) & 0xFF);
              }
          }
          else
          {
              out = new Mat(240, 320, CvType.CV_8UC1);
              data = new byte[320 * 240 * (int)out.elemSize()];
              int[] dataBuff = in.getRGB(0, 0, 320, 240, null, 0, 320);
              for(int i = 0; i < dataBuff.length; i++)
              {
                r = (byte) ((dataBuff[i] >> 16) & 0xFF);
                g = (byte) ((dataBuff[i] >> 8) & 0xFF);
                b = (byte) ((dataBuff[i] >> 0) & 0xFF);
                data[i] = (byte)((0.21 * r) + (0.71 * g) + (0.07 * b)); //luminosity
              }
           }
           out.put(0, 0, data);
           return out;
     }