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423 lines
13 KiB
C++
423 lines
13 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "precomp.hpp"
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#include <stdio.h>
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namespace cv
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{
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static void
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calcMinEigenVal( const Mat& _cov, Mat& _dst )
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{
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int i, j;
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Size size = _cov.size();
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#if CV_SSE
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volatile bool simd = checkHardwareSupport(CV_CPU_SSE);
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#endif
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if( _cov.isContinuous() && _dst.isContinuous() )
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{
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size.width *= size.height;
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size.height = 1;
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}
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for( i = 0; i < size.height; i++ )
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{
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const float* cov = (const float*)(_cov.data + _cov.step*i);
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float* dst = (float*)(_dst.data + _dst.step*i);
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j = 0;
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#if CV_SSE
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if( simd )
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{
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__m128 half = _mm_set1_ps(0.5f);
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for( ; j <= size.width - 5; j += 4 )
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{
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__m128 t0 = _mm_loadu_ps(cov + j*3); // a0 b0 c0 x
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__m128 t1 = _mm_loadu_ps(cov + j*3 + 3); // a1 b1 c1 x
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__m128 t2 = _mm_loadu_ps(cov + j*3 + 6); // a2 b2 c2 x
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__m128 t3 = _mm_loadu_ps(cov + j*3 + 9); // a3 b3 c3 x
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__m128 a, b, c, t;
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t = _mm_unpacklo_ps(t0, t1); // a0 a1 b0 b1
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c = _mm_unpackhi_ps(t0, t1); // c0 c1 x x
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b = _mm_unpacklo_ps(t2, t3); // a2 a3 b2 b3
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c = _mm_movelh_ps(c, _mm_unpackhi_ps(t2, t3)); // c0 c1 c2 c3
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a = _mm_movelh_ps(t, b);
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b = _mm_movehl_ps(b, t);
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a = _mm_mul_ps(a, half);
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c = _mm_mul_ps(c, half);
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t = _mm_sub_ps(a, c);
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t = _mm_add_ps(_mm_mul_ps(t, t), _mm_mul_ps(b,b));
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a = _mm_sub_ps(_mm_add_ps(a, c), _mm_sqrt_ps(t));
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_mm_storeu_ps(dst + j, a);
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}
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}
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#endif
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for( ; j < size.width; j++ )
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{
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float a = cov[j*3]*0.5f;
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float b = cov[j*3+1];
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float c = cov[j*3+2]*0.5f;
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dst[j] = (float)((a + c) - std::sqrt((a - c)*(a - c) + b*b));
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}
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}
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}
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static void
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calcHarris( const Mat& _cov, Mat& _dst, double k )
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{
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int i, j;
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Size size = _cov.size();
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#if CV_SSE
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volatile bool simd = checkHardwareSupport(CV_CPU_SSE);
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#endif
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if( _cov.isContinuous() && _dst.isContinuous() )
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{
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size.width *= size.height;
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size.height = 1;
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}
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for( i = 0; i < size.height; i++ )
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{
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const float* cov = (const float*)(_cov.data + _cov.step*i);
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float* dst = (float*)(_dst.data + _dst.step*i);
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j = 0;
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#if CV_SSE
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if( simd )
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{
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__m128 k4 = _mm_set1_ps((float)k);
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for( ; j <= size.width - 5; j += 4 )
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{
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__m128 t0 = _mm_loadu_ps(cov + j*3); // a0 b0 c0 x
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__m128 t1 = _mm_loadu_ps(cov + j*3 + 3); // a1 b1 c1 x
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__m128 t2 = _mm_loadu_ps(cov + j*3 + 6); // a2 b2 c2 x
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__m128 t3 = _mm_loadu_ps(cov + j*3 + 9); // a3 b3 c3 x
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__m128 a, b, c, t;
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t = _mm_unpacklo_ps(t0, t1); // a0 a1 b0 b1
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c = _mm_unpackhi_ps(t0, t1); // c0 c1 x x
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b = _mm_unpacklo_ps(t2, t3); // a2 a3 b2 b3
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c = _mm_movelh_ps(c, _mm_unpackhi_ps(t2, t3)); // c0 c1 c2 c3
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a = _mm_movelh_ps(t, b);
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b = _mm_movehl_ps(b, t);
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t = _mm_add_ps(a, c);
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a = _mm_sub_ps(_mm_mul_ps(a, c), _mm_mul_ps(b, b));
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t = _mm_mul_ps(_mm_mul_ps(k4, t), t);
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a = _mm_sub_ps(a, t);
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_mm_storeu_ps(dst + j, a);
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}
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}
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#endif
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for( ; j < size.width; j++ )
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{
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float a = cov[j*3];
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float b = cov[j*3+1];
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float c = cov[j*3+2];
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dst[j] = (float)(a*c - b*b - k*(a + c)*(a + c));
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}
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}
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}
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static void eigen2x2( const float* cov, float* dst, int n )
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{
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for( int j = 0; j < n; j++ )
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{
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double a = cov[j*3];
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double b = cov[j*3+1];
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double c = cov[j*3+2];
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double u = (a + c)*0.5;
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double v = std::sqrt((a - c)*(a - c)*0.25 + b*b);
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double l1 = u + v;
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double l2 = u - v;
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double x = b;
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double y = l1 - a;
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double e = fabs(x);
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if( e + fabs(y) < 1e-4 )
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{
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y = b;
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x = l1 - c;
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e = fabs(x);
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if( e + fabs(y) < 1e-4 )
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{
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e = 1./(e + fabs(y) + FLT_EPSILON);
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x *= e, y *= e;
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}
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}
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double d = 1./std::sqrt(x*x + y*y + DBL_EPSILON);
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dst[6*j] = (float)l1;
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dst[6*j + 2] = (float)(x*d);
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dst[6*j + 3] = (float)(y*d);
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x = b;
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y = l2 - a;
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e = fabs(x);
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if( e + fabs(y) < 1e-4 )
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{
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y = b;
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x = l2 - c;
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e = fabs(x);
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if( e + fabs(y) < 1e-4 )
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{
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e = 1./(e + fabs(y) + FLT_EPSILON);
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x *= e, y *= e;
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}
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}
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d = 1./std::sqrt(x*x + y*y + DBL_EPSILON);
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dst[6*j + 1] = (float)l2;
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dst[6*j + 4] = (float)(x*d);
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dst[6*j + 5] = (float)(y*d);
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}
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}
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static void
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calcEigenValsVecs( const Mat& _cov, Mat& _dst )
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{
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Size size = _cov.size();
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if( _cov.isContinuous() && _dst.isContinuous() )
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{
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size.width *= size.height;
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size.height = 1;
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}
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for( int i = 0; i < size.height; i++ )
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{
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const float* cov = (const float*)(_cov.data + _cov.step*i);
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float* dst = (float*)(_dst.data + _dst.step*i);
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eigen2x2(cov, dst, size.width);
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}
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}
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enum { MINEIGENVAL=0, HARRIS=1, EIGENVALSVECS=2 };
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static void
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cornerEigenValsVecs( const Mat& src, Mat& eigenv, int block_size,
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int aperture_size, int op_type, double k=0.,
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int borderType=BORDER_DEFAULT )
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{
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#ifdef HAVE_TEGRA_OPTIMIZATION
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if (tegra::cornerEigenValsVecs(src, eigenv, block_size, aperture_size, op_type, k, borderType))
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return;
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#endif
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int depth = src.depth();
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double scale = (double)(1 << ((aperture_size > 0 ? aperture_size : 3) - 1)) * block_size;
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if( aperture_size < 0 )
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scale *= 2.;
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if( depth == CV_8U )
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scale *= 255.;
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scale = 1./scale;
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CV_Assert( src.type() == CV_8UC1 || src.type() == CV_32FC1 );
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Mat Dx, Dy;
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if( aperture_size > 0 )
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{
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Sobel( src, Dx, CV_32F, 1, 0, aperture_size, scale, 0, borderType );
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Sobel( src, Dy, CV_32F, 0, 1, aperture_size, scale, 0, borderType );
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}
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else
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{
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Scharr( src, Dx, CV_32F, 1, 0, scale, 0, borderType );
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Scharr( src, Dy, CV_32F, 0, 1, scale, 0, borderType );
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}
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Size size = src.size();
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Mat cov( size, CV_32FC3 );
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int i, j;
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for( i = 0; i < size.height; i++ )
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{
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float* cov_data = (float*)(cov.data + i*cov.step);
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const float* dxdata = (const float*)(Dx.data + i*Dx.step);
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const float* dydata = (const float*)(Dy.data + i*Dy.step);
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for( j = 0; j < size.width; j++ )
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{
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float dx = dxdata[j];
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float dy = dydata[j];
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cov_data[j*3] = dx*dx;
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cov_data[j*3+1] = dx*dy;
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cov_data[j*3+2] = dy*dy;
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}
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}
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boxFilter(cov, cov, cov.depth(), Size(block_size, block_size),
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Point(-1,-1), false, borderType );
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if( op_type == MINEIGENVAL )
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calcMinEigenVal( cov, eigenv );
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else if( op_type == HARRIS )
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calcHarris( cov, eigenv, k );
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else if( op_type == EIGENVALSVECS )
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calcEigenValsVecs( cov, eigenv );
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}
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}
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void cv::cornerMinEigenVal( InputArray _src, OutputArray _dst, int blockSize, int ksize, int borderType )
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{
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Mat src = _src.getMat();
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_dst.create( src.size(), CV_32F );
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Mat dst = _dst.getMat();
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cornerEigenValsVecs( src, dst, blockSize, ksize, MINEIGENVAL, 0, borderType );
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}
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void cv::cornerHarris( InputArray _src, OutputArray _dst, int blockSize, int ksize, double k, int borderType )
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{
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Mat src = _src.getMat();
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_dst.create( src.size(), CV_32F );
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Mat dst = _dst.getMat();
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cornerEigenValsVecs( src, dst, blockSize, ksize, HARRIS, k, borderType );
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}
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void cv::cornerEigenValsAndVecs( InputArray _src, OutputArray _dst, int blockSize, int ksize, int borderType )
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{
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Mat src = _src.getMat();
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Size dsz = _dst.size();
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int dtype = _dst.type();
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if( dsz.height != src.rows || dsz.width*CV_MAT_CN(dtype) != src.cols*6 || CV_MAT_DEPTH(dtype) != CV_32F )
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_dst.create( src.size(), CV_32FC(6) );
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Mat dst = _dst.getMat();
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cornerEigenValsVecs( src, dst, blockSize, ksize, EIGENVALSVECS, 0, borderType );
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}
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void cv::preCornerDetect( InputArray _src, OutputArray _dst, int ksize, int borderType )
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{
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Mat Dx, Dy, D2x, D2y, Dxy, src = _src.getMat();
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CV_Assert( src.type() == CV_8UC1 || src.type() == CV_32FC1 );
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_dst.create( src.size(), CV_32F );
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Mat dst = _dst.getMat();
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Sobel( src, Dx, CV_32F, 1, 0, ksize, 1, 0, borderType );
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Sobel( src, Dy, CV_32F, 0, 1, ksize, 1, 0, borderType );
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Sobel( src, D2x, CV_32F, 2, 0, ksize, 1, 0, borderType );
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Sobel( src, D2y, CV_32F, 0, 2, ksize, 1, 0, borderType );
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Sobel( src, Dxy, CV_32F, 1, 1, ksize, 1, 0, borderType );
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double factor = 1 << (ksize - 1);
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if( src.depth() == CV_8U )
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factor *= 255;
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factor = 1./(factor * factor * factor);
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Size size = src.size();
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int i, j;
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for( i = 0; i < size.height; i++ )
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{
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float* dstdata = (float*)(dst.data + i*dst.step);
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const float* dxdata = (const float*)(Dx.data + i*Dx.step);
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const float* dydata = (const float*)(Dy.data + i*Dy.step);
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const float* d2xdata = (const float*)(D2x.data + i*D2x.step);
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const float* d2ydata = (const float*)(D2y.data + i*D2y.step);
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const float* dxydata = (const float*)(Dxy.data + i*Dxy.step);
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for( j = 0; j < size.width; j++ )
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{
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float dx = dxdata[j];
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float dy = dydata[j];
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dstdata[j] = (float)(factor*(dx*dx*d2ydata[j] + dy*dy*d2xdata[j] - 2*dx*dy*dxydata[j]));
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}
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}
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}
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CV_IMPL void
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cvCornerMinEigenVal( const CvArr* srcarr, CvArr* dstarr,
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int block_size, int aperture_size )
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{
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cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
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CV_Assert( src.size() == dst.size() && dst.type() == CV_32FC1 );
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cv::cornerMinEigenVal( src, dst, block_size, aperture_size, cv::BORDER_REPLICATE );
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}
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CV_IMPL void
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cvCornerHarris( const CvArr* srcarr, CvArr* dstarr,
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int block_size, int aperture_size, double k )
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{
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cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
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CV_Assert( src.size() == dst.size() && dst.type() == CV_32FC1 );
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cv::cornerHarris( src, dst, block_size, aperture_size, k, cv::BORDER_REPLICATE );
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}
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CV_IMPL void
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cvCornerEigenValsAndVecs( const void* srcarr, void* dstarr,
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int block_size, int aperture_size )
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{
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cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
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CV_Assert( src.rows == dst.rows && src.cols*6 == dst.cols*dst.channels() && dst.depth() == CV_32F );
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cv::cornerEigenValsAndVecs( src, dst, block_size, aperture_size, cv::BORDER_REPLICATE );
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}
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CV_IMPL void
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cvPreCornerDetect( const void* srcarr, void* dstarr, int aperture_size )
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{
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cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
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CV_Assert( src.size() == dst.size() && dst.type() == CV_32FC1 );
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cv::preCornerDetect( src, dst, aperture_size, cv::BORDER_REPLICATE );
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}
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/* End of file */
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