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更新裁切纠偏算法到最新版本

This commit is contained in:
yangjiaxuan 2023-11-28 15:47:34 +08:00
parent 7de96f6dff
commit 9e30fa0db0
2 changed files with 45 additions and 41 deletions
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35
hgdriver/ImageProcess/ImageApplyAutoCrop.cpp
View File

@ -4,7 +4,6 @@
#include <opencv2/imgproc/hal/hal.hpp> #include <opencv2/imgproc/hal/hal.hpp>
#include "ImageApplyDispersion.h" #include "ImageApplyDispersion.h"
#define COLOR_BACKGROUND_THRE 20
#define FRONT_TOP 70 #define FRONT_TOP 70
#define FX_FY 0.5f #define FX_FY 0.5f
@ -18,14 +17,13 @@ CImageApplyAutoCrop::CImageApplyAutoCrop()
, m_noise(8) , m_noise(8)
, m_indent(5) , m_indent(5)
, m_normalCrop(false) , m_normalCrop(false)
, m_isDispersion(true)
, m_fx(1.0) , m_fx(1.0)
, m_fy(1.0) , m_fy(1.0)
{ {
} }
CImageApplyAutoCrop::CImageApplyAutoCrop(bool isCrop, bool isDesaskew, bool isFillBlank, const cv::Size& fixedSize, bool isConvex, bool isFillColor, CImageApplyAutoCrop::CImageApplyAutoCrop(bool isCrop, bool isDesaskew, bool isFillBlank, const cv::Size& fixedSize, bool isConvex, bool isFillColor,
double threshold, int noise, int indent, bool normalCrop, bool dispersion, double fx, double fy) double threshold, int noise, int indent, bool normalCrop, double fx, double fy)
: m_isCrop(isCrop) : m_isCrop(isCrop)
, m_isDesaskew(isDesaskew) , m_isDesaskew(isDesaskew)
, m_isFillBlank(isFillBlank) , m_isFillBlank(isFillBlank)
@ -36,7 +34,6 @@ CImageApplyAutoCrop::CImageApplyAutoCrop(bool isCrop, bool isDesaskew, bool isFi
, m_indent(indent) , m_indent(indent)
, m_fixedSize(fixedSize) , m_fixedSize(fixedSize)
, m_normalCrop(normalCrop) , m_normalCrop(normalCrop)
, m_isDispersion(dispersion)
, m_fx(fx) , m_fx(fx)
, m_fy(fy) , m_fy(fy)
{ {
@ -50,7 +47,7 @@ void CImageApplyAutoCrop::apply(cv::Mat& pDib, int side)
{ {
cv::Mat dst; cv::Mat dst;
autoCrop_desaskew_fillBlank(pDib, dst, m_isCrop, m_isDesaskew, m_isFillBlank, m_fixedSize.width, m_fixedSize.height, autoCrop_desaskew_fillBlank(pDib, dst, m_isCrop, m_isDesaskew, m_isFillBlank, m_fixedSize.width, m_fixedSize.height,
m_isConvexHull, m_isFillColor, m_threshold, m_noise, m_indent, m_normalCrop, m_isDispersion, m_fx, m_fy); m_isConvexHull, m_isFillColor, m_threshold, m_noise, m_indent, m_normalCrop, m_fx, m_fy);
pDib = dst; pDib = dst;
} }
@ -99,14 +96,14 @@ void CImageApplyAutoCrop::myWarpAffine(cv::InputArray _src, cv::OutputArray _dst
M, interpolation, borderType, borderValue.val); M, interpolation, borderType, borderValue.val);
} }
cv::Scalar CImageApplyAutoCrop::getBackGroudColor(const cv::Mat& image, int threshold) cv::Scalar CImageApplyAutoCrop::getBackGroudColor(const cv::Mat& image)
{ {
if (image.channels() == 3) if (image.channels() == 3)
{ {
uchar table[768] = { 0 }; uchar table[768] = { 0 };
int hist_bgr[3][256] = { 0 }; int hist_bgr[3][256] = { 0 };
int width = image.cols, height = image.rows, bytesPerLine = image.step; int width = image.cols, height = image.rows, bytesPerLine = image.step;
memset(table + threshold * 3, 255, 768 - threshold * 3); memset(table, 255, 768);
unsigned char* ptr_data = image.data; unsigned char* ptr_data = image.data;
unsigned char b = 0; unsigned char b = 0;
@ -136,7 +133,7 @@ cv::Scalar CImageApplyAutoCrop::getBackGroudColor(const cv::Mat& image, int thre
uchar table[256] = { 0 }; uchar table[256] = { 0 };
int hist_bgr[256] = { 0 }; int hist_bgr[256] = { 0 };
int width = image.cols, height = image.rows, bytesPerLine = image.step; int width = image.cols, height = image.rows, bytesPerLine = image.step;
memset(table + threshold, 255, 256 - threshold); memset(table, 255, 256);
unsigned char* ptr_data = image.data; unsigned char* ptr_data = image.data;
unsigned char b = 0; unsigned char b = 0;
for (uint i = 0; i < height; i++, ptr_data += bytesPerLine) for (uint i = 0; i < height; i++, ptr_data += bytesPerLine)
@ -153,7 +150,7 @@ cv::Scalar CImageApplyAutoCrop::getBackGroudColor(const cv::Mat& image, int thre
} }
void CImageApplyAutoCrop::autoCrop_desaskew_fillBlank(cv::Mat& src, cv::Mat& dst, bool isAutoCrop, bool isDesaskew, bool isFillBlank, int dWidth, int dHeight, void CImageApplyAutoCrop::autoCrop_desaskew_fillBlank(cv::Mat& src, cv::Mat& dst, bool isAutoCrop, bool isDesaskew, bool isFillBlank, int dWidth, int dHeight,
bool isConvex, bool isColorBlank, double threshold, int noise, int indent, bool isNormalCrop, bool dispersion, double fx, double fy) bool isConvex, bool isColorBlank, double threshold, int noise, int indent, bool isNormalCrop, double fx, double fy)
{ {
if (src.empty()) return; if (src.empty()) return;
@ -186,7 +183,7 @@ void CImageApplyAutoCrop::autoCrop_desaskew_fillBlank(cv::Mat& src, cv::Mat& dst
hg::threshold_Mat(resizeMat, thre, threshold); hg::threshold_Mat(resizeMat, thre, threshold);
if (noise > 0) if (noise > 0)
cv::morphologyEx(thre, thre, cv::MORPH_OPEN, getStructuringElement(cv::MORPH_RECT, cv::Size(noise * FX_FY, 1)), cv::morphologyEx(thre, thre, cv::MORPH_OPEN, getStructuringElement(cv::MORPH_RECT, cv::Size(cv::max(static_cast<int>(noise * FX_FY), 1), 1)),
cv::Point(-1, -1), 1, cv::BORDER_CONSTANT, cv::Scalar::all(0)); cv::Point(-1, -1), 1, cv::BORDER_CONSTANT, cv::Scalar::all(0));
std::vector<cv::Vec4i> hierarchy; std::vector<cv::Vec4i> hierarchy;
@ -213,18 +210,24 @@ void CImageApplyAutoCrop::autoCrop_desaskew_fillBlank(cv::Mat& src, cv::Mat& dst
} }
cv::RotatedRect rect = hg::getBoundingRect(maxContour); cv::RotatedRect rect = hg::getBoundingRect(maxContour);
if (rect.size.width < 1 || rect.size.height < 1)
if (dispersion)
{ {
CImageApplyDispersion m_dispersion_apply; dst = src;
cv::Mat mat_dispersion = src(cv::boundingRect(maxContour)); return;
m_dispersion_apply.apply(mat_dispersion, 0);
} }
cv::Scalar blankColor; cv::Scalar blankColor;
if (isFillBlank) if (isFillBlank)
if (isColorBlank) if (isColorBlank)
blankColor = getBackGroudColor(resizeMat, COLOR_BACKGROUND_THRE); {
cv::Rect boudingRect = cv::boundingRect(maxContour);
boudingRect.x *= FX_FY;
boudingRect.y *= FX_FY;
boudingRect.width *= FX_FY;
boudingRect.height *= FX_FY;
blankColor = getBackGroudColor(resizeMat(boudingRect));
}
else else
blankColor = cv::Scalar::all(255); blankColor = cv::Scalar::all(255);
else else

51
hgdriver/ImageProcess/ImageApplyAutoCrop.h
View File

@ -2,8 +2,8 @@
* ==================================================== * ====================================================
* 功能：自动裁剪、纠偏、除黑底 * 功能：自动裁剪、纠偏、除黑底
* 作者：刘丁绿 * 作者：刘丁维
* 生成时间＿020/4/21 * 生成时间：2020/4/21
* 最近修改时间：2020/4/21 v1.0 * 最近修改时间：2020/4/21 v1.0
2020/7/22 v1.1 增加获取图像有效区域轮廓的接口maxContour（用于配合一体机的“跳过空白页”算法，PC端暂时无需使用＿ 2020/7/22 v1.1 增加获取图像有效区域轮廓的接口maxContour（用于配合一体机的“跳过空白页”算法，PC端暂时无需使用＿
2020/10/16 v1.2 修复自动裁剪尺寸精度丢失的BUG；提高除黑底缩进精度 2020/10/16 v1.2 修复自动裁剪尺寸精度丢失的BUG；提高除黑底缩进精度
@ -29,7 +29,12 @@
2022/10/31 v1.5 增加横纵DPI缩放参数fx,fy。 2022/10/31 v1.5 增加横纵DPI缩放参数fx,fy。
2022/11/19 v1.5.1 修复文稿背景色识别算法的BUG。 2022/11/19 v1.5.1 修复文稿背景色识别算法的BUG。
2022/11/19 v1.5.2 修复灰度文稿背景色识别算法的BUG。 2022/11/19 v1.5.2 修复灰度文稿背景色识别算法的BUG。
* 版本号：v1.5.2 2023/03/17 v1.5.3 修复背景除噪时，形态学处理kSize可能为0的BUG。
2023/04/19 v1.5.4 取消集成色散功能。
2023/05/15 v1.5.5 优化文稿背景色识别算法。
2023/05/23 v1.5.6 修复纯黑图找不到外界轮廓会导致崩溃的BUG。
2023/11/02 v1.6 优化抗噪能力。采用自适应背景色二值化。
* 版本号：v1.5.6
* ==================================================== * ====================================================
*/ */
@ -39,29 +44,28 @@
#include "ImageApply.h" #include "ImageApply.h"
class CImageApplyDispersion;
class GIMGPROC_LIBRARY_API CImageApplyAutoCrop : public CImageApply class GIMGPROC_LIBRARY_API CImageApplyAutoCrop : public CImageApply
{ {
public: public:
CImageApplyAutoCrop(); CImageApplyAutoCrop();
/* /// <summary>
* isCrop [in]:自动幅面裁剪使能，true自动裁剪，false为固定裁剿 /// 构造函数
* isDesaskew [in]:自动纠偏使能，true自动纠偏，false为不纠偏 /// </summary>
* isFillBlank [in]:黑底填充使能，true为填充，false为不填充 /// <param name="isCrop">自动幅面裁剪使能，true自动裁剪，false为固定裁切</param>
* fixedSize [in]:固定幅面尺寸，当isCrop为false时生效，结果尺寸按fixedSize大小输出，单位像紿 /// <param name="isDesaskew">自动纠偏使能，true自动纠偏，false为不纠偏</param>
* isConvex [in]:黑底填充时的填充方式,true为凸多边形填充，false为凹多边形填充，默认true /// <param name="isFillBlank">黑底填充使能，true为填充，false为不填充</param>
* isFillColor [in]:黑底填充时采用自适应色彩填充，false为白色填充，true为自适应文稿底色填充，默认false /// <param name="fixedSize">固定幅面尺寸，当isCrop为false时生效，结果尺寸按fixedSize大小输出，单位像素</param>
* threshold [in]:二值化阈值，取值范囿0, 255)，默访0 /// <param name="isConvex">黑底填充时的填充方式,true为凸多边形填充，false为凹多边形填充，默认true</param>
* noise [in]:除噪像素，能够消除noise宽度的背景竖条纹干扰，默访 /// <param name="isFillColor">黑底填充时采用自适应色彩填充，false为白色填充，true为自适应文稿底色填充，默认false</param>
* indent [in]:轮廓缩进，裁剪、纠偏或者黑底填充时，对探索到的纸张轮廓进行缩进indent像素，默访 /// <param name="threshold">二值化阈值，取值范囿[-1, 255]，默认40。当threshold<0时，采用根据背景自适应二值化。</param>
* normalCrop [in]:为true时，m_isCrop m_isDesaskew m_isFillBlank失效，固定裁切采用最传统的裁切方式，默认false /// <param name="noise">除噪像素，能够消除noise宽度的背景竖条纹干扰，默认8。</param>
* dispersion [in]:为true时，除色散；false时不除色散。默认为true /// <param name="indent">轮廓缩进，裁剪、纠偏或者黑底填充时，对探索到的纸张轮廓进行缩进indent像素，默认8</param>
* fx [in]:横向缩放比例。默认1.0 /// <param name="normalCrop">为true时，m_isCrop m_isDesaskew m_isFillBlank失效，固定裁切采用最传统的裁切方式，默认false</param>
* fy [in]:纵向缩放比例。默认1.0 /// <param name="fx">横向缩放比例。默认1.0</param>
*/ /// <param name="fy">纵向缩放比例。默认1.0</param>
CImageApplyAutoCrop(bool isCrop, bool isDesaskew, bool isFillBlank, const cv::Size& fixedSize, bool isConvex = true, CImageApplyAutoCrop(bool isCrop, bool isDesaskew, bool isFillBlank, const cv::Size& fixedSize, bool isConvex = true,
bool isFillColor = false, double threshold = 40, int noise = 8, int indent = 5, bool normalCrop = false, bool dispersion = true, double fx = 1.0, double fy = 1.0); bool isFillColor = false, double threshold = 40, int noise = 8, int indent = 5, bool normalCrop = false, double fx = 1.0, double fy = 1.0);
virtual ~CImageApplyAutoCrop(); virtual ~CImageApplyAutoCrop();
@ -105,23 +109,20 @@ public:
void setFixedSize(cv::Size size) { m_fixedSize = size; } void setFixedSize(cv::Size size) { m_fixedSize = size; }
void setDispersion(bool enable) { m_isDispersion = enable; }
static void autoCrop_desaskew_fillBlank(cv::Mat& src, cv::Mat& dst, bool isAutoCrop, bool isDesaskew, bool isFillBlank, int dWidth, int dHeight, static void autoCrop_desaskew_fillBlank(cv::Mat& src, cv::Mat& dst, bool isAutoCrop, bool isDesaskew, bool isFillBlank, int dWidth, int dHeight,
bool isConvex = true, bool isColorBlank = false, double threshold = 40, int noise = 8, int indent = 5, bool isNormalCrop = false, bool dispersion = true, bool isConvex = true, bool isColorBlank = false, double threshold = 40, int noise = 8, int indent = 5, bool isNormalCrop = false,
double fx = 1.0, double fy = 1.0); double fx = 1.0, double fy = 1.0);
private: private:
static void myWarpAffine(cv::InputArray _src, cv::OutputArray _dst, cv::InputArray _M0, cv::Size dsize, int flags, int borderType, const cv::Scalar& borderValue); static void myWarpAffine(cv::InputArray _src, cv::OutputArray _dst, cv::InputArray _M0, cv::Size dsize, int flags, int borderType, const cv::Scalar& borderValue);
static cv::Scalar getBackGroudColor(const cv::Mat& image, int threshold); static cv::Scalar getBackGroudColor(const cv::Mat& image);
private: private:
bool m_isCrop; bool m_isCrop;
bool m_isDesaskew; bool m_isDesaskew;
bool m_isFillBlank; bool m_isFillBlank;
bool m_isConvexHull; bool m_isConvexHull;
bool m_isFillColor; bool m_isFillColor;
bool m_isDispersion;
double m_threshold; double m_threshold;
int m_noise; int m_noise;