2022-07-29 08:41:34 +00:00
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/*
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* ====================================================
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* 功能：二值化处理
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* 作者：刘丁维
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* 生成时间：2020/4/21
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* 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
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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
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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
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2020/12/21 v1.3.1 调整自适应阈值上下限
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2020/12/21 v1.3.2 调整blockSize,从原来的51调整到25
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2022/05/25 v1.3.3 调整blockSize和constant，对THRESH_BINARY同样有效
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2023-11-22 07:37:50 +00:00
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2023/11/22 v1.4 当THRESH_BINARY模式时，参数m_threshold作为THRESHOLD_LOW使用。
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* 版本号：v1.4
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2022-07-29 08:41:34 +00:00
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* ====================================================
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*/
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#ifndef IMAGE_APPLY_BW_BINARAY_H
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#define IMAGE_APPLY_BW_BINARAY_H
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#include "ImageApply.h"
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class GIMGPROC_LIBRARY_API CImageApplyBWBinaray:public CImageApply
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{
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public:
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enum class ThresholdType
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{
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THRESH_BINARY = 0, //传统二值化
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THRESH_OTSU, //大津阈值
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ADAPTIVE_GAUSSIAN, //高斯局部自适应阈值
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ADAPTIVE_MEAN, //均值局部自适应阈值
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ERROR_DIFFUSION //错误扩散
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};
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/*
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* type [in]:二值化模式
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* threshold [in]:阈值，当选择THRESH_OTSU时无效
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* blockSize [in]:ADAPTIVE_GAUSSIAN和ADAPTIVE_MEAN模式有效，表示局部观察块的宽度
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* 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
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*/
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CImageApplyBWBinaray(ThresholdType type, int threshold = 120, int blockSize = 51, int constant = 41);
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CImageApplyBWBinaray();
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virtual ~CImageApplyBWBinaray(void);
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virtual void apply(cv::Mat& pDib,int side);
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virtual void apply(std::vector<cv::Mat>& mats, bool isTwoSide);
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double getThreshold() { return m_threshold; }
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ThresholdType getThresholdType() { return m_type; }
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int getBlockSize() { return m_blockSize; }
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double getConstant() { return m_constant; }
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void setThreshold(double value) { m_threshold = value; }
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void setThresholdType(ThresholdType type) { m_type = type; }
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void setBlockSize(int value) { m_blockSize = value; }
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void setConstant(double value) { m_constant = value; }
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private:
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void errorDiffuse(cv::Mat& image);
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private:
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double m_threshold;
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ThresholdType m_type;
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int m_blockSize;
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double m_constant;
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uchar* m_table;
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};
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#endif //!IMAGE_APPLY_BW_BINARAY_H
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