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Started porting the camera calibration functions.

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This commit is contained in:
Wally Hackenslacker
2014-04-10 17:55:31 -04:30
parent 453c3a36e5
commit 249e6e30a4
6 changed files with 493 additions and 380 deletions
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2
jni/Android.mk
View File

@@ -4,7 +4,7 @@ include $(CLEAR_VARS)
OPENCV_CAMERA_MODULES:=off
OPENCV_LIB_TYPE:=STATIC
include /home/miky/Escritorio/OpenCV-2.4.7-android-sdk/sdk/native/jni/OpenCV.mk
include C:\Users\miguel.astor\Documents\OpenCV-2.4.8-android-sdk\sdk\native\jni\OpenCV.mk
LOCAL_MODULE := cvproc
LOCAL_SRC_FILES := cv_proc.cpp marker.cpp

58
jni/cv_proc.cpp
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@@ -21,8 +21,6 @@
//#define CAN_LOG
extern "C"{
#ifdef CAN_LOG
#define log(TAG, MSG) (__android_log_write(ANDROID_LOG_DEBUG, TAG, MSG))
const char * TAG = "CVPROC_NATIVE";
@@ -30,57 +28,61 @@ const char * TAG = "CVPROC_NATIVE";
#define log(TAG, MSG) (1 + 1)
#endif
JNIEXPORT void JNICALL Java_ve_ucv_ciens_ccg_nxtar_MainActivity_getMarkerCodesAndLocations(
JNIEnv* env,
jobject jobj,
jlong addrMatIn,
jlong addrMatOut,
jintArray codes
){
extern "C"{
JNIEXPORT void JNICALL Java_ve_ucv_ciens_ccg_nxtar_MainActivity_getMarkerCodesAndLocations(JNIEnv* env, jobject jobj, jlong addrMatIn, jlong addrMatOut, jintArray codes){
char codeMsg[128];
std::vector<int> vCodes;
log(TAG, "Requesting native data.");
log(TAG, "getMarkerCodesAndLocations(): Requesting native data.");
cv::Mat& myuv = *(cv::Mat*)addrMatIn;
cv::Mat& mbgr = *(cv::Mat*)addrMatOut;
jint * _codes = env->GetIntArrayElements(codes, 0);
jint * _codes = env->GetIntArrayElements(codes, 0);
log(TAG, "Converting color space before processing.");
log(TAG, "getMarkerCodesAndLocations(): Converting color space before processing.");
cv::cvtColor(myuv, mbgr, CV_RGB2BGR);
log(TAG, "Finding markers.");
log(TAG, "getMarkerCodesAndLocations(): Finding markers.");
nxtar::getAllMarkers(vCodes, mbgr);
log(TAG, "Copying marker codes.");
log(TAG, "getMarkerCodesAndLocations(): Copying marker codes.");
for(int i = 0; i < vCodes.size() && i < 15; i++){
_codes[i] = vCodes[i];
sprintf(codeMsg, "Code [%d] = %d", i, vCodes[i]);
log(TAG, codeMsg);
_codes[i] = (jint)vCodes[i];
}
vCodes.clear();
log(TAG, "Releasing native data.");
log(TAG, "getMarkerCodesAndLocations(): Releasing native data.");
env->ReleaseIntArrayElements(codes, _codes, 0);
}
JNIEXPORT void JNICALL Java_ve_ucv_ciens_ccg_nxtar_MainActivity_findCalibrationPattern(
JNIEnv* env,
jobject jobj,
jlong addrMatIn,
jlong addrMatOut
){
log(TAG, "Requesting native data.");
JNIEXPORT jboolean JNICALL Java_ve_ucv_ciens_ccg_nxtar_MainActivity_findCalibrationPattern(JNIEnv* env, jobject jobj, jlong addrMatIn, jlong addrMatOut, jfloatArray points){
nxtar::points_vector v_points;
bool found;
log(TAG, "findCalibrationPattern(): Requesting native data.");
cv::Mat& myuv = *(cv::Mat*)addrMatIn;
cv::Mat& mbgr = *(cv::Mat*)addrMatOut;
jfloat * _points = env->GetFloatArrayElements(points, 0);
log(TAG, "Converting color space before processing.");
log(TAG, "findCalibrationPattern(): Converting color space before processing.");
cv::cvtColor(myuv, mbgr, CV_RGB2BGR);
log(TAG, "Finding markers.");
nxtar::calibrateCamera(mbgr);
log(TAG, "findCalibrationPattern(): Finding calibration pattern.");
found = nxtar::findCalibrationPattern(v_points, mbgr);
log(TAG, "findCalibrationPattern(): Copying calibration points.");
for(size_t i = 0, p = 0; i < v_points.size(); i++, p += 2){
_points[p] = (jfloat)v_points[i].x;
_points[p + 1] = (jfloat)v_points[i].y;
}
log(TAG, "findCalibrationPattern(): Releasing native data.");
env->ReleaseFloatArrayElements(points, _points, 0);
return (jboolean)found;
}
}

722
jni/marker.cpp
View File

@@ -16,331 +16,451 @@
#include <algorithm>
#include <utility>
#include <limits>
#ifdef DESKTOP
#include <iostream>
#endif
#include "marker.hpp"
#define MIN_CONTOUR_LENGTH 0.1
namespace nxtar{
static int PATTERN_DETECTION_PARAMS = cv::CALIB_CB_ADAPTIVE_THRESH + cv::CALIB_CB_NORMALIZE_IMAGE + cv::CALIB_CB_FAST_CHECK;
static const cv::TermCriteria termCriteria = cv::TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 30, 0.1);
static const cv::Scalar COLOR = cv::Scalar(255, 255, 255);
static const cv::Size checkersPatternSize(6, 9);
typedef std::vector<cv::Point3f> points_vector_3D;
typedef std::vector<std::vector<cv::Point> > contours_vector;
typedef std::vector<Marker> markers_vector;
float perimeter (points_vector &);
int hammDistMarker (cv::Mat);
cv::Mat rotate (cv::Mat);
int decodeMarker (cv::Mat &);
void renderMarkers (markers_vector &, cv::Mat &);
void isolateMarkers (const contours_vector &, markers_vector &);
void findContours (cv::Mat &, contours_vector &, int);
void warpMarker (Marker &, cv::Mat &, cv::Mat &);
/******************************************************************************
* PRIVATE CONSTANTS *
******************************************************************************/
void getAllMarkers(std::vector<int> & codes, cv::Mat & img){
cv::Mat gray, thresh, cont, mark;
contours_vector contours;
markers_vector markers;
markers_vector valid_markers;
/**
* Size of a square cell in the calibration pattern.
*/
static const float SQUARE_SIZE = 1.0f;
/**
* Minimal lenght of a contour to be considered as a marker candidate.
*/
static const float MIN_CONTOUR_LENGTH = 0.1;
/**
* Flags for the calibration pattern detecion function.
*/
static const int PATTERN_DETECTION_FLAGS = cv::CALIB_CB_ADAPTIVE_THRESH + cv::CALIB_CB_NORMALIZE_IMAGE + cv::CALIB_CB_FAST_CHECK;
/**
* Color for rendering the marker outlines.
*/
static const cv::Scalar COLOR = cv::Scalar(255, 255, 255);
/**
* Size of the chessboard pattern image (columns, rows).
*/
static const cv::Size CHESSBOARD_PATTERN_SIZE(6, 9);
/**
* Termination criteria for OpenCV's iterative algorithms.
*/
static const cv::TermCriteria TERM_CRITERIA = cv::TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 30, 0.1);
/******************************************************************************
* PRIVATE FUNCTION PROTOTYPES *
******************************************************************************/
/**
* Calculates the perimeter of a points vector defining a polygon.
*/
float perimeter(points_vector &);
/**
* Calculates the Hamming distance of a 5x5 marker.
*/
int hammDistMarker(cv::Mat);
/**
* Rotates an OpenCV matrix in place by 90 degrees clockwise.
*/
cv::Mat rotate(cv::Mat);
/**
* Returns the code of a 5x5 marker or -1 if the marker is not valid.
*/
int decodeMarker(cv::Mat &);
/**
* Renders the polygon defined in the input vector on the specified image.
*/
void renderMarkers(markers_vector &, cv::Mat &);
/**
* Identifies all possible marker candidates in a polygon vector.
*/
void isolateMarkers(const contours_vector &, markers_vector &);
/**
* Identifies all roughly 4 side figures in the input image.
*/
void findContours(cv::Mat &, contours_vector &, int);
/**
* Removes the prerspective distortion from a marker candidate image.
*/
void warpMarker(Marker &, cv::Mat &, cv::Mat &);
/******************************************************************************
* PUBLIC API *
******************************************************************************/
void getAllMarkers(std::vector<int> & codes, cv::Mat & img){
cv::Mat gray, thresh, cont, mark;
contours_vector contours;
markers_vector markers;
markers_vector valid_markers;
#ifdef DESKTOP
std::ostringstream oss;
std::ostringstream oss;
#endif
codes.clear();
codes.clear();
cv::cvtColor(img, gray, CV_BGR2GRAY);
cv::adaptiveThreshold(gray, thresh, 255, cv::ADAPTIVE_THRESH_MEAN_C, cv::THRESH_BINARY_INV, 7, 7);
findContours(thresh, contours, 40);
isolateMarkers(contours, markers);
// Find all marker candidates in the input image.
// 1) First, convert the image to grayscale.
// 2) Then, binarize the grayscale image.
// 3) Finally indentify all 4 sided figures in the binarized image.
cv::cvtColor(img, gray, CV_BGR2GRAY);
cv::adaptiveThreshold(gray, thresh, 255, cv::ADAPTIVE_THRESH_MEAN_C, cv::THRESH_BINARY_INV, 7, 7);
findContours(thresh, contours, 40);
isolateMarkers(contours, markers);
for(int i = 0; i < markers.size(); i++){
warpMarker(markers[i], gray, mark);
// Remove the perspective distortion from the detected marker candidates.
// Then attempt to decode them and push the valid ones into the valid
// markes vector.
for(int i = 0; i < markers.size(); i++){
warpMarker(markers[i], gray, mark);
int code = decodeMarker(mark);
int code = decodeMarker(mark);
if(code != -1){
markers[i].code = code;
valid_markers.push_back(markers[i]);
}
}
if(code != -1){
markers[i].code = code;
valid_markers.push_back(markers[i]);
}
}
for(int i = 0; i < valid_markers.size(); i++){
for(int i = 0; i < valid_markers.size(); i++){
#ifdef DESKTOP
oss << valid_markers[i].code;
// Render the detected valid markers with their codes for debbuging
// purposes.
oss << valid_markers[i].code;
cv::putText(mark, oss.str(), cv::Point(5, 250), cv::FONT_HERSHEY_PLAIN, 2, cv::Scalar::all(128), 3, 8);
cv::putText(mark, oss.str(), cv::Point(5, 250), cv::FONT_HERSHEY_PLAIN, 2, cv::Scalar::all(128), 3, 8);
oss.str("");
oss.clear();
oss.str("");
oss.clear();
oss << "Marker[" << i << "]";
oss << "Marker[" << i << "]";
cv::imshow(oss.str(), mark);
cv::imshow(oss.str(), mark);
oss.str("");
oss.clear();
oss.str("");
oss.clear();
#endif
cv::cornerSubPix(gray, valid_markers[i].points, cvSize(10, 10), cvSize(-1, -1), termCriteria);
codes.push_back(valid_markers[i].code);
}
// Fix the detected corners to better approximate the markers. And
// push their codes to the output vector.
cv::cornerSubPix(gray, valid_markers[i].points, cvSize(10, 10), cvSize(-1, -1), TERM_CRITERIA);
codes.push_back(valid_markers[i].code);
}
cont = cv::Mat::zeros(img.size(), CV_8UC3);
renderMarkers(valid_markers, cont);
// Render the detected markers on top of the input image.
cont = cv::Mat::zeros(img.size(), CV_8UC3);
renderMarkers(valid_markers, cont);
img = img + cont;
img = img + cont;
markers.clear();
contours.clear();
valid_markers.clear();
}
void calibrateCamera(cv::Mat & img){
bool patternfound;
points_vector corners;
cv::Mat gray;
cv::cvtColor(img, gray, CV_BGR2GRAY);
patternfound = cv::findChessboardCorners(gray, checkersPatternSize, corners, PATTERN_DETECTION_PARAMS);
if(patternfound)
cv::cornerSubPix(gray, corners, cv::Size(11, 11), cv::Size(-1, -1), termCriteria);
cv::drawChessboardCorners(img, checkersPatternSize, cv::Mat(corners), patternfound);
}
void findContours(cv::Mat & img, contours_vector & v, int minP){
std::vector<std::vector<cv::Point> > c;
cv::findContours(img, c, CV_RETR_LIST, CV_CHAIN_APPROX_NONE);
v.clear();
for(size_t i = 0; i < c.size(); i++){
if(c[i].size() > minP){
v.push_back(c[i]);
}
}
}
void renderMarkers(markers_vector & v, cv::Mat & dst){
contours_vector cv;
for(size_t i = 0; i < v.size(); i++){
std::vector<cv::Point> pv;
for(size_t j = 0; j < v[i].points.size(); ++j)
pv.push_back(cv::Point2f(v[i].points[j].x, v[i].points[j].y));
cv.push_back(pv);
}
cv::drawContours(dst, cv, -1, COLOR, 1, CV_AA);
}
void isolateMarkers(const contours_vector & vc, markers_vector & vm){
std::vector<cv::Point> appCurve;
markers_vector posMarkers;
for(size_t i = 0; i < vc.size(); ++i){
double eps = vc[i].size() * 0.05;
cv::approxPolyDP(vc[i], appCurve, eps, true);
if(appCurve.size() != 4 || !cv::isContourConvex(appCurve)) continue;
float minD = std::numeric_limits<float>::max();
for(int i = 0; i < 4; i++){
cv::Point side = appCurve[i] - appCurve[(i + 1) % 4];
float sqSideLen = side.dot(side);
minD = std::min(minD, sqSideLen);
}
if(minD < MIN_CONTOUR_LENGTH) continue;
Marker m;
for(int i = 0; i < 4; i++)
m.points.push_back(cv::Point2f(appCurve[i].x, appCurve[i].y));
cv::Point v1 = m.points[1] - m.points[0];
cv::Point v2 = m.points[2] - m.points[0];
double o = (v1.x * v2.y) - (v1.y * v2.x);
if(o < 0.0) std::swap(m.points[1], m.points[3]);
posMarkers.push_back(m);
}
std::vector<std::pair<int, int> > tooNear;
for(size_t i = 0; i < posMarkers.size(); ++i){
const Marker & m1 = posMarkers[i];
for(size_t j = i + 1; j < posMarkers.size(); j++){
const Marker & m2 = posMarkers[j];
float dSq = 0.0f;
for(int c = 0; c < 4; c++){
cv::Point v = m1.points[c] - m2.points[c];
dSq += v.dot(v);
}
dSq /= 4.0f;
if(dSq < 100) tooNear.push_back(std::pair<int, int>(i, j));
}
}
std::vector<bool> remMask(posMarkers.size(), false);
for(size_t i = 0; i < tooNear.size(); ++i){
float p1 = perimeter(posMarkers[tooNear[i].first].points);
float p2 = perimeter(posMarkers[tooNear[i].second].points);
size_t remInd;
if(p1 > p2) remInd = tooNear[i].second;
else remInd = tooNear[i].first;
remMask[remInd] = true;
}
vm.clear();
for(size_t i = 0; i < posMarkers.size(); ++i){
if(remMask[i]) vm.push_back(posMarkers[i]);
}
}
void warpMarker(Marker & m, cv::Mat & in, cv::Mat & out){
cv::Mat bin;
cv::Size markerSize(350, 350);
points_vector v;
v.push_back(cv::Point2f(0,0));
v.push_back(cv::Point2f(markerSize.width-1,0));
v.push_back(cv::Point2f(markerSize.width-1,markerSize.height-1));
v.push_back(cv::Point2f(0,markerSize.height-1));
cv::Mat M = cv::getPerspectiveTransform(m.points, v);
cv::warpPerspective(in, bin, M, markerSize);
cv::threshold(bin, out, 128, 255, cv::THRESH_BINARY | cv::THRESH_OTSU);
}
int hammDistMarker(cv::Mat bits){
int ids[4][5] = {
{1,0,0,0,0},
{1,0,1,1,1},
{0,1,0,0,1},
{0,1,1,1,0}
};
int dist = 0;
for (int y = 0; y < 5; y++){
int minSum = 1e5;
for (int p = 0; p < 4; p++){
int sum = 0;
for (int x = 0; x < 5; x++){
sum += bits.at<uchar>(y, x) == ids[p][x] ? 0 : 1;
}
if(minSum > sum)
minSum = sum;
}
dist += minSum;
}
return dist;
}
cv::Mat rotate(cv::Mat in){
cv::Mat out;
in.copyTo(out);
for (int i=0;i<in.rows;i++){
for (int j=0;j<in.cols;j++){
out.at<uchar>(i,j)=in.at<uchar>(in.cols-j-1,i);
}
}
return out;
}
int decodeMarker(cv::Mat & marker){
bool found = false;
int code = 0;
cv::Mat bits;
for(int y = 0; y < 7; y++){
int inc = (y == 0 || y == 6) ? 1 : 6;
for(int x = 0; x < 7; x += inc){
int cX = x * 50;
int cY = y * 50;
cv::Mat cell = marker(cv::Rect(cX, cY, 50, 50));
int nZ = cv::countNonZero(cell);
// Not a valid marker.
if(nZ > (50 * 50) / 2) return -1;
}
}
bits = cv::Mat::zeros(5, 5, CV_8UC1);
for(int y = 0; y < 5; y++){
for(int x = 0; x < 5; x++){
int cX = (x + 1) * 50;
int cY = (y + 1) * 50;
cv::Mat cell = marker(cv::Rect(cX, cY, 50, 50));
int nZ = cv::countNonZero(cell);
if(nZ > (50 * 50) / 2) bits.at<uchar>(y, x) = 1;
}
}
if(hammDistMarker(bits) != 0){
for(int r = 1; r < 4; r++){
bits = rotate(bits);
if(hammDistMarker(bits) != 0) continue;
else{ found = true; break;}
}
}else found = true;
if(found){
for(int y = 0; y < 5; y++){
code <<= 1;
if(bits.at<uchar>(y, 1))
code |= 1;
code <<= 1;
if(bits.at<uchar>(y, 3))
code |= 1;
}
return code;
}else
return -1;
}
float perimeter(points_vector & p){
float per = 0.0f, dx, dy;
for(size_t i; i < p.size(); ++i){
dx = p[i].x - p[(i + 1) % p.size()].x;
dy = p[i].y - p[(i + 1) % p.size()].y;
per += sqrt((dx * dx) + (dy * dy));
}
return per;
}
Marker::~Marker(){
points.clear();
}
// Clear the local vectors.
markers.clear();
contours.clear();
valid_markers.clear();
}
bool findCalibrationPattern(points_vector & corners, cv::Mat & img){
bool patternfound;
cv::Mat gray;
// Convert the input image to grayscale and attempt to find the
// calibration pattern.
cv::cvtColor(img, gray, CV_BGR2GRAY);
patternfound = cv::findChessboardCorners(gray, CHESSBOARD_PATTERN_SIZE, corners, PATTERN_DETECTION_FLAGS);
// If the pattern was found then fix the detected points a bit.
if(patternfound)
cv::cornerSubPix(gray, corners, cv::Size(11, 11), cv::Size(-1, -1), TERM_CRITERIA);
// Render the detected pattern.
cv::drawChessboardCorners(img, CHESSBOARD_PATTERN_SIZE, cv::Mat(corners), patternfound);
return patternfound;
}
double getCameraParameters(cv::Mat & camera_matrix, cv::Mat & dist_coeffs, std::vector<points_vector> & image_points, cv::Size image_size){
std::vector<cv::Mat> rvecs, tvecs;
std::vector<points_vector_3D> object_points;
points_vector_3D corner_points;
// Build the reference object points vector;
for(int i = 0; i < CHESSBOARD_PATTERN_SIZE.height; i++){
for(int j = 0; j < CHESSBOARD_PATTERN_SIZE.width; j++){
corner_points.push_back(cv::Point3f(float( j * SQUARE_SIZE ), float( i * SQUARE_SIZE ), 0));
}
}
object_points.push_back(corner_points);
object_points.resize(image_points.size(), object_points[0]);
// Build a camera matrix.
camera_matrix = cv::Mat::eye(3, 3, CV_64F);
// Build the distortion coefficients matrix.
dist_coeffs = cv::Mat::zeros(8, 1, CV_64F);
// Calibrate and return the reprojection error.
return cv::calibrateCamera(object_points, image_points, image_size, camera_matrix, dist_coeffs, rvecs, tvecs, 0, TERM_CRITERIA);
}
/******************************************************************************
* PRIVATE HELPER FUNCTIONS *
******************************************************************************/
void findContours(cv::Mat & img, contours_vector & v, int minP){
contours_vector c;
cv::findContours(img, c, CV_RETR_LIST, CV_CHAIN_APPROX_NONE);
v.clear();
for(size_t i = 0; i < c.size(); i++){
if(c[i].size() > minP){
v.push_back(c[i]);
}
}
}
void renderMarkers(markers_vector & v, cv::Mat & dst){
contours_vector cv;
for(size_t i = 0; i < v.size(); i++){
std::vector<cv::Point> pv;
for(size_t j = 0; j < v[i].points.size(); ++j)
pv.push_back(cv::Point2f(v[i].points[j].x, v[i].points[j].y));
cv.push_back(pv);
}
cv::drawContours(dst, cv, -1, COLOR, 1, CV_AA);
}
void isolateMarkers(const contours_vector & vc, markers_vector & vm){
std::vector<cv::Point> appCurve;
markers_vector posMarkers;
for(size_t i = 0; i < vc.size(); ++i){
double eps = vc[i].size() * 0.05;
cv::approxPolyDP(vc[i], appCurve, eps, true);
if(appCurve.size() != 4 || !cv::isContourConvex(appCurve)) continue;
float minD = std::numeric_limits<float>::max();
for(int i = 0; i < 4; i++){
cv::Point side = appCurve[i] - appCurve[(i + 1) % 4];
float sqSideLen = side.dot(side);
minD = std::min(minD, sqSideLen);
}
if(minD < MIN_CONTOUR_LENGTH) continue;
Marker m;
for(int i = 0; i < 4; i++)
m.points.push_back(cv::Point2f(appCurve[i].x, appCurve[i].y));
cv::Point v1 = m.points[1] - m.points[0];
cv::Point v2 = m.points[2] - m.points[0];
double o = (v1.x * v2.y) - (v1.y * v2.x);
if(o < 0.0) std::swap(m.points[1], m.points[3]);
posMarkers.push_back(m);
}
std::vector<std::pair<int, int> > tooNear;
for(size_t i = 0; i < posMarkers.size(); ++i){
const Marker & m1 = posMarkers[i];
for(size_t j = i + 1; j < posMarkers.size(); j++){
const Marker & m2 = posMarkers[j];
float dSq = 0.0f;
for(int c = 0; c < 4; c++){
cv::Point v = m1.points[c] - m2.points[c];
dSq += v.dot(v);
}
dSq /= 4.0f;
if(dSq < 100) tooNear.push_back(std::pair<int, int>(i, j));
}
}
std::vector<bool> remMask(posMarkers.size(), false);
for(size_t i = 0; i < tooNear.size(); ++i){
float p1 = perimeter(posMarkers[tooNear[i].first].points);
float p2 = perimeter(posMarkers[tooNear[i].second].points);
size_t remInd;
if(p1 > p2) remInd = tooNear[i].second;
else remInd = tooNear[i].first;
remMask[remInd] = true;
}
vm.clear();
for(size_t i = 0; i < posMarkers.size(); ++i){
if(remMask[i]) vm.push_back(posMarkers[i]);
}
}
void warpMarker(Marker & m, cv::Mat & in, cv::Mat & out){
cv::Mat bin;
cv::Size markerSize(350, 350);
points_vector v;
v.push_back(cv::Point2f(0,0));
v.push_back(cv::Point2f(markerSize.width-1,0));
v.push_back(cv::Point2f(markerSize.width-1,markerSize.height-1));
v.push_back(cv::Point2f(0,markerSize.height-1));
cv::Mat M = cv::getPerspectiveTransform(m.points, v);
cv::warpPerspective(in, bin, M, markerSize);
cv::threshold(bin, out, 128, 255, cv::THRESH_BINARY | cv::THRESH_OTSU);
}
int hammDistMarker(cv::Mat bits){
int ids[4][5] = {
{1,0,0,0,0},
{1,0,1,1,1},
{0,1,0,0,1},
{0,1,1,1,0}
};
int dist = 0;
for (int y = 0; y < 5; y++){
int minSum = 1e5;
for (int p = 0; p < 4; p++){
int sum = 0;
for (int x = 0; x < 5; x++){
sum += bits.at<uchar>(y, x) == ids[p][x] ? 0 : 1;
}
if(minSum > sum)
minSum = sum;
}
dist += minSum;
}
return dist;
}
cv::Mat rotate(cv::Mat in){
cv::Mat out;
in.copyTo(out);
for (int i=0;i<in.rows;i++){
for (int j=0;j<in.cols;j++){
out.at<uchar>(i,j)=in.at<uchar>(in.cols-j-1,i);
}
}
return out;
}
int decodeMarker(cv::Mat & marker){
bool found = false;
int code = 0;
cv::Mat bits;
for(int y = 0; y < 7; y++){
int inc = (y == 0 || y == 6) ? 1 : 6;
for(int x = 0; x < 7; x += inc){
int cX = x * 50;
int cY = y * 50;
cv::Mat cell = marker(cv::Rect(cX, cY, 50, 50));
int nZ = cv::countNonZero(cell);
// Not a valid marker.
if(nZ > (50 * 50) / 2) return -1;
}
}
bits = cv::Mat::zeros(5, 5, CV_8UC1);
for(int y = 0; y < 5; y++){
for(int x = 0; x < 5; x++){
int cX = (x + 1) * 50;
int cY = (y + 1) * 50;
cv::Mat cell = marker(cv::Rect(cX, cY, 50, 50));
int nZ = cv::countNonZero(cell);
if(nZ > (50 * 50) / 2) bits.at<uchar>(y, x) = 1;
}
}
if(hammDistMarker(bits) != 0){
for(int r = 1; r < 4; r++){
bits = rotate(bits);
if(hammDistMarker(bits) != 0) continue;
else{ found = true; break;}
}
}else found = true;
if(found){
for(int y = 0; y < 5; y++){
code <<= 1;
if(bits.at<uchar>(y, 1))
code |= 1;
code <<= 1;
if(bits.at<uchar>(y, 3))
code |= 1;
}
return code;
}else
return -1;
}
float perimeter(points_vector & p){
float per = 0.0f, dx, dy;
for(size_t i; i < p.size(); ++i){
dx = p[i].x - p[(i + 1) % p.size()].x;
dy = p[i].y - p[(i + 1) % p.size()].y;
per += sqrt((dx * dx) + (dy * dy));
}
return per;
}
/******************************************************************************
* CLASS METHODS *
******************************************************************************/
Marker::~Marker(){
points.clear();
}
}

27
jni/marker.hpp
View File

@@ -17,15 +17,12 @@
#define MARKER_HPP
#include <vector>
#include <opencv2/opencv.hpp>
namespace nxtar{
class Marker;
typedef std::vector<std::vector<cv::Point> > contours_vector;
typedef std::vector<cv::Point2f> points_vector;
typedef std::vector<Marker> markers_vector;
typedef std::vector<cv::Point2f> points_vector;
class Marker{
public:
@@ -34,8 +31,26 @@ public:
int code;
};
/**
* Detect all 5x5 markers in the input image and return their codes in the
* output vector.
*/
void getAllMarkers(std::vector<int> &, cv::Mat &);
void calibrateCamera(cv::Mat &);
/**
* Find a chessboard calibration pattern in the input image. Returns true
* if the pattern was found, false otherwise. The calibration points
* detected on the image are saved in the output vector.
*/
bool findCalibrationPattern(points_vector &, cv::Mat &);
/**
* Sets the camera matrix and the distortion coefficients for the camera
* that captured the input image points into the output matrices. Returns
* the reprojection error as returned by cv::calibrateCamera.
*/
double getCameraParameters(cv::Mat &, cv::Mat &, std::vector<points_vector> &, cv::Size);
}
#endif