基于c语言图像边缘检测的程序,图像边缘检测之拉普拉斯(Laplacian)C++实现
拉普拉斯算子(Laplacian)可應用到圖像邊緣檢測中。在OpenCV中當kernel大小為3*3時，支持兩種kernel算子，分別為：
在OpenCV中默認的計算方式如下，假設有一個5*5的小圖像，原始值依次為1,2,…25,如下圖紅色部分，首先將5*5映射到(5+3-1)*(5+3-1)大小，然后和3*3的kernel做累積和，因為計算結果有可能超出有效值[0, 255]范圍，因此在最終還需要判斷使其在有效范圍內，即小于0為0，大于255為255：
如坐標為(0,0)的計算過程為：12 = 7*0+6*1+7*0+2*1+1*(-4)+2*1+7*0+6*1+7*0.
以下code分別采用兩種方式實現，一種是從OpenCV中提取的code(Laplacian_函數)，一種是按照上面說明的方式實現的(Laplacian函數)，兩種方式實現的結果完全一致，但第二種方式更容易理解：
laplacian.cpp:#include?"funset.hpp"
#include?
#include?
#include?
#include?
#include?
#include?"common.hpp"
namespace?{
typedef?struct?Rect?{
int?x,?y,?width,?height;
}?Rect;
typedef?struct?Size?{
int?width,?height;
}?Size;
typedef?struct?Point?{
int?x,?y;
}?Point;
int?borderInterpolate(int?p,?int?len)
{
if?((unsigned)p?
;
}?else?{
if?(len?==?1)?return?0;
int?delta?=?1;
do?{
if?(p?
else?p?=?len?-?1?-?(p?-?len)?-?delta;
}?while?((unsigned)p?>=?(unsigned)len);
}
return?p;
}
inline?unsigned?char?saturate_cast(float?v)
{
int?iv?=?(int)(v?+?(v?>=?0???0.5f?:?-0.5f));
return?(unsigned?char)((unsigned)v?<=?UCHAR_MAX???v?:?v?>?0???UCHAR_MAX?:?0);
}
void?filter2D(const?unsigned?char**?src,?unsigned?char*?dst,?int?dststep,?int?count,?int?width,?int?ksize)
{
std::vector?coords;
std::vector?coeffs;
if?(ksize?==?1)?{
coords?=?{?{?1,?0?},?{?0,?1?},?{?1,?1?},?{?2,?1?},?{?1,?2?}?};?//?kernel?non?zero?position:?(x,?y)
coeffs?=?{?1.f,?1.f,?-4.f,?1.f,?1.f?};?//?kernel?non?zero?value:?1,?1,?-4,?1,?1
}?else?{
coords?=?{?{?0,?0?},?{?2,?0?},?{?1,?1?},?{?0,?2?},?{?2,?2?}?};?//?kernel?non?zero?position:?(x,?y)
coeffs?=?{?2.f,?2.f,?-8.f,?2.f,?2.f?};?//?kernel?non?zero?value:?2,?2,?-8,?2,?2
}
std::vector?ptrs(coords.size());
float?_delta{?0.f?};
const?Point*?pt?=?&coords[0];
const?float*?kf?=?(const?float*)&coeffs[0];
const?unsigned?char**?kp?=?(const?unsigned?char**)&ptrs[0];
int?nz?=?(int)coords.size();
for?(;?count?>?0;?count--,?dst?+=?dststep,?src++)?{
unsigned?char*?D?=?(unsigned?char*)dst;
for?(int?k?=?0;?k?
kp[k]?=?(const?unsigned?char*)src[pt[k].y]?+?pt[k].x;
for?(int?i?=?0;?i?
float?s0?=?_delta;
for?(int?k?=?0;?k?
s0?+=?kf[k]?*?kp[k][i];
D[i]?=?saturate_cast(s0);
}
}
}
int?Laplacian_(const?unsigned?char*?src_,?unsigned?char*?dst_,?int?width_,?int?height_,?int?ksize_)
{
const?unsigned?char*?src?=?src_;
unsigned?char*?dst?=?dst_;
const?Size?ksize{?3,?3?};
const?int?maxBufRows?=?ksize.height?+?3;
const?Point?anchor{?1,?1?};
const?Rect?roi{?0,?0,?width_,?height_?};
const?int?dx1{?1?},?dx2{?1?};
int?borderLength?=?std::max(ksize.width?-?1,?1);
std::vector?borderTab(borderLength);
borderTab[0]?=?borderInterpolate(-dx1,?width_);
borderTab[1]?=?borderInterpolate(width_,?width_);
std::vector?rows(maxBufRows);
const?int*?btab?=?&borderTab[0];
int?srcstep{?width_?},?dststep{?width_?};
std::vector?ringBuf((width_?+?ksize.width?-?1)?*?maxBufRows,?0);
int?bufStep{?width_?+?ksize.width?-?1?};
int?startY?=?std::max(roi.y?-?anchor.y,?0),?startY0?=?startY,?rowCount{?0?},?dstY{?0?};
int?endY?=?std::min(roi.y?+?roi.height?+?ksize.height?-?anchor.y?-?1,?height_);
int?esz?=?1;
unsigned?char**?brows?=?&rows[0];
int?bufRows?=?(int)rows.size();
int?kwidth?=?ksize.width;
int?kheight?=?ksize.height,?ay?=?anchor.y;
int?_dx1?=?dx1,?_dx2?=?dx2;
int?width1?=?roi.width?+?kwidth?-?1;
int?dy?=?0,?i?=?0;
int?count?=?endY?-?startY;
for?(;;?dst?+=?dststep?*?i,?dy?+=?i)?{
int?dcount?=?bufRows?-?ay?-?startY?-?rowCount?+?roi.y;
dcount?=?dcount?>?0???dcount?:?bufRows?-?kheight?+?1;
dcount?=?std::min(dcount,?count);
count?-=?dcount;
for?(;?dcount--?>?0;?src?+=?srcstep)?{
int?bi?=?(startY?-?startY0?+?rowCount)?%?bufRows;
unsigned?char*?brow?=?&ringBuf[0]?+?bi*bufStep;
unsigned?char*?row?=?brow;
if?(++rowCount?>?bufRows)?{
--rowCount;
++startY;
}
memcpy(row?+?_dx1*esz,?src,?(width1?-?_dx2?-?_dx1)*esz);
for?(i?=?0;?i?
row[i]?=?src[btab[i]];
for?(i?=?0;?i?
row[i?+?(width1?-?_dx2)*esz]?=?src[btab[i?+?_dx1*esz]];
}
int?max_i?=?std::min(bufRows,?roi.height?-?(dstY?+?dy)?+?(kheight?-?1));
for?(i?=?0;?i?
int?srcY?=?borderInterpolate(dstY?+?dy?+?i?+?roi.y?-?ay,?height_);
if?(srcY?
if?(srcY?>=?startY?+?rowCount)?break;
int?bi?=?(srcY?-?startY0)?%?bufRows;
brows[i]?=?&ringBuf[0]?+?bi*bufStep;
}
if?(i?
i?-=?kheight?-?1;
filter2D((const?unsigned?char**)brows,?dst,?dststep,?i,?roi.width,?ksize_);
}
dstY?+=?dy;
if?(dstY?>?roi.height)?return?-1;
return?0;
}
int?Laplacian(const?unsigned?char*?src_,?unsigned?char*?dst_,?int?width_,?int?height_,?int?ksize_)
{
const?int?kernel_size{?3?};
std::vector?kernel;
if?(ksize_?==?1)?kernel?=?{?0.f,?1.f,?0.f,?1.f,?-4.f,?1.f,?0.f,?1.f,?0.f?};
else?kernel?=?{?2.f,?0.f,?2.f,?0.f,?-8.f,?0.f,?2.f,?0.f,?2.f?};
int?new_width?=?width_?+?kernel_size?-?1,?new_height?=?height_?+?kernel_size?-?1;
std::unique_ptr?data(new?unsigned?char[new_width?*?new_height]);
unsigned?char*?p?=?data.get();
for?(int?y?=?0;?y?
if?(y?!=?0?&&?y?!=?new_height?-?1)?{
for?(int?x?=?0;?x?
if?(x?==?0)?{
p[y?*?new_width?+?x]?=?src_[(y?-?1)?*?width_?+?1];
}?else?if?(x?==?new_width?-?1)?{
p[y?*?new_width?+?x]?=?src_[(y?-?1)?*?width_?+?(width_?-?1?-?1)];
}?else?{
p[y?*?new_width?+?x]?=?src_[(y?-?1)?*?width_?+?(x?-?1)];
}
}
}
if?(y?==?new_height?-?1)?{
for?(int?x?=?0;?x?
p[y?*?new_width?+?x]?=?p[(y?-?2)?*?new_width?+?x];
}
for?(int?x?=?0;?x?
p[x]?=?p[2?*?new_width?+?x];
}
}
}
for?(int?y?=?1;?y?
for?(int?x?=?1;?x?
float?value{?0.f?};
int?count{?0?};
for?(int?m?=?-1;?m?<=?1;?++m)?{
for?(int?n?=?-1;?n?<=?1;?++n)?{
value?+=?p[(y?+?m)?*?new_width?+?(x?+?n)]?*?kernel[count++];
}
}
if?(value?
else?if?(value?>?255.)?dst_[(y?-?1)?*?width_?+?(x?-?1)]?=?255;
else?dst_[(y?-?1)?*?width_?+?(x?-?1)]?=?static_cast(value);
}
}
return?0;
}
}?//?namespace
int?laplacian_cpu(const?unsigned?char*?src,?int?width,?int?height,?int?ksize,?unsigned?char*?dst,?float*?elapsed_time)
{
int?ret{?-1?};
//?ksize?==?1:?kernel={?0,?1,?0,?1,?-4,?1,?0,?1,?0?}
//?ksize?==?3:?kernel={?2,?0,?2,?0,?-8,?0,?2,?0,?2?}
CHECK(ksize?==?1?||?ksize?==?3);
//TIME_START_CPU
ret?=?Laplacian(src,?dst,?width,?height,?ksize);
//TIME_END_CPU
return?ret;
}
main.cpp:#include?"funset.hpp"
#include?
#include?
#include?
#include?
#include?
#include?
#include?"common.hpp"
int?test_image_process_laplacian()
{
cv::Mat?src?=?cv::imread("E:/GitCode/CUDA_Test/test_data/images/lena.png",?0);
if?(!src.data?||?src.channels()?!=?1)?{
fprintf(stderr,?"read?image?fail\n");
return?-1;
}
int?width{?400?},?height{?400?};
cv::resize(src,?src,?cv::Size(width,?height));
std::unique_ptr?data1(new?unsigned?char[width?*?height]),?data2(new?unsigned?char[width?*?height]);
float?elapsed_time1{?0.f?},?elapsed_time2{?0.f?};?//?milliseconds
int?ksize{?1?};
CHECK(laplacian_cpu(src.data,?width,?height,?ksize,?data1.get(),?&elapsed_time1)?==?0);
//CHECK(laplacian_gpu(src.data,?width,?height,?data2.get(),?&elapsed_time2)?==?0);
//fprintf(stdout,?"gray?image?edge?detection:?laplacian:?cpu?run?time:?%f?ms,?gpu?run?time:?%f?ms\n",?elapsed_time1,?elapsed_time2);
cv::Mat?dst;
cv::Laplacian(src,?dst,?src.depth(),?ksize);
cv::imwrite("E:/GitCode/CUDA_Test/test_data/images/laplacian.png",?dst);
CHECK(compare_result(data1.get(),?dst.data,?width*height)?==?0);
//CHECK(compare_result(data1.get(),?data2.get(),?width*height)?==?0);
save_image(src,?dst,?width,?height?/?2,?"E:/GitCode/CUDA_Test/test_data/images/laplacian_result.png");
return?0;
}
執行結果如下：
由結果可知：C++實現結果和調用OpenCV的接口結果是完全一致的。
總結
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