twain3.0/huagao/ImageProcess/ImageApplyBWBinaray.h

/*
 * ====================================================

 * 功能：二值化处理
 * 作者：刘丁维
 * 生成时间：2020/4/21
 * 最近修改时间：2020/5/28  v1.1 修改传统二值化算法，改用自定义局部自适应阈值算法
				 2020/5/29  v1.2 在传统二值化之前添加增强锐化效果，二值化之后增加除噪效果
				 2020/6/19  v1.3 编写自定义自适应阈值二值化；取消锐化处理；保留除噪效果
				 2020/12/21 v1.3.1 调整自适应阈值上下限
				 2020/12/21 v1.3.2 调整blockSize,从原来的51调整到25
 * 版本号：v1.3.2

 * ====================================================
 */

#ifndef IMAGE_APPLY_BW_BINARAY_H
#define IMAGE_APPLY_BW_BINARAY_H

#include "ImageApply.h"

class  CImageApplyBWBinaray:public CImageApply
{
public:

	enum class ThresholdType
	{
		THRESH_BINARY = 0,		//传统二值化
		THRESH_OTSU,			//大津阈值

		ADAPTIVE_GAUSSIAN,		//高斯局部自适应阈值
		ADAPTIVE_MEAN,			//均值局部自适应阈值

		ERROR_DIFFUSION			//错误扩散
	};

    /*
     * type      [in]:二值化模式
     * threshold [in]:阈值，当选择THRESH_OTSU时无效
     * blockSize [in]:ADAPTIVE_GAUSSIAN和ADAPTIVE_MEAN模式有效，表示局部观察块的宽度
     * constant  [in]:ADAPTIVE_GAUSSIAN和ADAPTIVE_MEAN模式有效，与blockSize形成比例关系，作为局部筛选阈值
     */
	CImageApplyBWBinaray(ThresholdType type, int threshold = 120, int blockSize = 25, int constant = 5);

	CImageApplyBWBinaray();

	virtual ~CImageApplyBWBinaray(void);

	virtual void apply(cv::Mat& pDib,int side);

	virtual void apply(std::vector<cv::Mat>& mats, bool isTwoSide);

	double getThreshold() { return m_threshold; }

	ThresholdType getThresholdType() { return m_type; }

	int getBlockSize() { return m_blockSize; }

	double getConstant() { return m_constant; }

	void setThreshold(double value) { m_threshold = value; }

	void setThresholdType(ThresholdType type) { m_type = type; }

	void setBlockSize(int value) { m_blockSize = value; }

	void setConstant(double value) { m_constant = value; }

private:

	void errorDiffuse(cv::Mat& image);

private:
	double m_threshold;

	ThresholdType m_type;

	int m_blockSize;

	double m_constant;

	uchar* m_table;
};

#endif //!IMAGE_APPLY_BW_BINARAY_H