WebSVN - OpenCV2-Cookbook - Diff - Rev 3 and 5 - /trunk/Chapter 04/objectFinder.h


#if !defined OFINDER
#define OFINDER

#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>

class ObjectFinder {

  private:

        float hranges[2];
    const float* ranges[3];
    int channels[3];

        float threshold;
        cv::MatND histogram;
        cv::SparseMat shistogram;
        bool isSparse;

  public:

        ObjectFinder() : threshold(0.1f), isSparse(false) {

                ranges[0]= hranges; // all channels have the same range 
                ranges[1]= hranges;
                ranges[2]= hranges;
        }
   
        // Sets the threshold on histogram values [0,1]
        void setThreshold(float t) {

                threshold= t;
        }

        // Gets the threshold
        float getThreshold() {

                return threshold;
        }

        // Sets the reference histogram
        void setHistogram(const cv::MatND& h) {

                isSparse= false;
                histogram= h;
                cv::normalize(histogram,histogram,1.0);
        }

        // Sets the reference histogram
        void setHistogram(const cv::SparseMat& h) {

                isSparse= true;
                shistogram= h;
                cv::normalize(shistogram,shistogram,1.0,cv::NORM_L2);
        }

        // Finds the pixels belonging to the histogram
        cv::Mat find(const cv::Mat& image) {

                cv::Mat result;

                hranges[0]= 0.0;        // range [0,255]
                hranges[1]= 255.0;
                channels[0]= 0;         // the three channels 
                channels[1]= 1;
                channels[2]= 2;

                if (isSparse) { // call the right function based on histogram type

                   cv::calcBackProject(&image,
                      1,            // one image
                      channels,     // vector specifying what histogram dimensions belong to what image channels
                      shistogram,   // the histogram we are using
                      result,       // the resulting back projection image
                      ranges,       // the range of values, for each dimension
                      255.0         // the scaling factor is chosen such that a histogram value of 1 maps to 255
                   );

                } else {

                   cv::calcBackProject(&image,
                      1,            // one image
                      channels,     // vector specifying what histogram dimensions belong to what image channels
                      histogram,    // the histogram we are using
                      result,       // the resulting back projection image
                      ranges,       // the range of values, for each dimension
                      255.0         // the scaling factor is chosen such that a histogram value of 1 maps to 255
                   );
                }


        // Threshold back projection to obtain a binary image
                if (threshold>0.0)
                        cv::threshold(result, result, 255*threshold, 255, cv::THRESH_BINARY);

                return result;
        }

        cv::Mat find(const cv::Mat& image, float minValue, float maxValue, int *channels, int dim) {

                cv::Mat result;

                hranges[0]= minValue;
                hranges[1]= maxValue;

                for (int i=0; i<dim; i++)
                        this->channels[i]= channels[i];

                if (isSparse) { // call the right function based on histogram type

                   cv::calcBackProject(&image,
                      1,            // we only use one image at a time
                      channels,     // vector specifying what histogram dimensions belong to what image channels
                      shistogram,   // the histogram we are using
                      result,       // the resulting back projection image
                      ranges,       // the range of values, for each dimension
                      255.0         // the scaling factor is chosen such that a histogram value of 1 maps to 255
                   );

                } else {

                   cv::calcBackProject(&image,
                      1,            // we only use one image at a time
                      channels,     // vector specifying what histogram dimensions belong to what image channels
                      histogram,    // the histogram we are using
                      result,       // the resulting back projection image
                      ranges,       // the range of values, for each dimension
                      255.0         // the scaling factor is chosen such that a histogram value of 1 maps to 255
                   );
                }

        // Threshold back projection to obtain a binary image
                if (threshold>0.0)
                        cv::threshold(result, result, 255*threshold, 255, cv::THRESH_BINARY);

                return result;
        }

};


#endif
 

Rev 3	Rev 5
1	#if !defined OFINDER	1	#if !defined OFINDER
2	#define OFINDER	2	#define OFINDER
3		3
4	#include <opencv2\core\core.hpp>	4	#include <opencv2/core/core.hpp>
5	#include <opencv2\imgproc\imgproc.hpp>	5	#include <opencv2/imgproc/imgproc.hpp>
6		6
7	class ObjectFinder {	7	class ObjectFinder {
8		8
9	private:	9	private:
10		10
11	float hranges[2];	11	float hranges[2];
12	const float* ranges[3];	12	const float* ranges[3];
13	int channels[3];	13	int channels[3];
14		14
15	float threshold;	15	float threshold;
16	cv::MatND histogram;	16	cv::MatND histogram;
17	cv::SparseMat shistogram;	17	cv::SparseMat shistogram;
18	bool isSparse;	18	bool isSparse;
19		19
20	public:	20	public:
21		21
22	ObjectFinder() : threshold(0.1f), isSparse(false) {	22	ObjectFinder() : threshold(0.1f), isSparse(false) {
23		23
24	ranges[0]= hranges; // all channels have the same range	24	ranges[0]= hranges; // all channels have the same range
25	ranges[1]= hranges;	25	ranges[1]= hranges;
26	ranges[2]= hranges;	26	ranges[2]= hranges;
27	}	27	}
28		28
29	// Sets the threshold on histogram values [0,1]	29	// Sets the threshold on histogram values [0,1]
30	void setThreshold(float t) {	30	void setThreshold(float t) {
31		31
32	threshold= t;	32	threshold= t;
33	}	33	}
34		34
35	// Gets the threshold	35	// Gets the threshold
36	float getThreshold() {	36	float getThreshold() {
37		37
38	return threshold;	38	return threshold;
39	}	39	}
40		40
41	// Sets the reference histogram	41	// Sets the reference histogram
42	void setHistogram(const cv::MatND& h) {	42	void setHistogram(const cv::MatND& h) {
43		43
44	isSparse= false;	44	isSparse= false;
45	histogram= h;	45	histogram= h;
46	cv::normalize(histogram,histogram,1.0);	46	cv::normalize(histogram,histogram,1.0);
47	}	47	}
48		48
49	// Sets the reference histogram	49	// Sets the reference histogram
50	void setHistogram(const cv::SparseMat& h) {	50	void setHistogram(const cv::SparseMat& h) {
51		51
52	isSparse= true;	52	isSparse= true;
53	shistogram= h;	53	shistogram= h;
54	cv::normalize(shistogram,shistogram,1.0,cv::NORM_L2);	54	cv::normalize(shistogram,shistogram,1.0,cv::NORM_L2);
55	}	55	}
56		56
57	// Finds the pixels belonging to the histogram	57	// Finds the pixels belonging to the histogram
58	cv::Mat find(const cv::Mat& image) {	58	cv::Mat find(const cv::Mat& image) {
59		59
60	cv::Mat result;	60	cv::Mat result;
61		61
62	hranges[0]= 0.0; // range [0,255]	62	hranges[0]= 0.0; // range [0,255]
63	hranges[1]= 255.0;	63	hranges[1]= 255.0;
64	channels[0]= 0; // the three channels	64	channels[0]= 0; // the three channels
65	channels[1]= 1;	65	channels[1]= 1;
66	channels[2]= 2;	66	channels[2]= 2;
67		67
68	if (isSparse) { // call the right function based on histogram type	68	if (isSparse) { // call the right function based on histogram type
69		69
70	cv::calcBackProject(&image,	70	cv::calcBackProject(&image,
71	1, // one image	71	1, // one image
72	channels, // vector specifying what histogram dimensions belong to what image channels	72	channels, // vector specifying what histogram dimensions belong to what image channels
73	shistogram, // the histogram we are using	73	shistogram, // the histogram we are using
74	result, // the resulting back projection image	74	result, // the resulting back projection image
75	ranges, // the range of values, for each dimension	75	ranges, // the range of values, for each dimension
76	255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255	76	255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255
77	);	77	);
78		78
79	} else {	79	} else {
80		80
81	cv::calcBackProject(&image,	81	cv::calcBackProject(&image,
82	1, // one image	82	1, // one image
83	channels, // vector specifying what histogram dimensions belong to what image channels	83	channels, // vector specifying what histogram dimensions belong to what image channels
84	histogram, // the histogram we are using	84	histogram, // the histogram we are using
85	result, // the resulting back projection image	85	result, // the resulting back projection image
86	ranges, // the range of values, for each dimension	86	ranges, // the range of values, for each dimension
87	255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255	87	255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255
88	);	88	);
89	}	89	}
90		90
91		91
92	// Threshold back projection to obtain a binary image	92	// Threshold back projection to obtain a binary image
93	if (threshold>0.0)	93	if (threshold>0.0)
94	cv::threshold(result, result, 255*threshold, 255, cv::THRESH_BINARY);	94	cv::threshold(result, result, 255*threshold, 255, cv::THRESH_BINARY);
95		95
96	return result;	96	return result;
97	}	97	}
98		98
99	cv::Mat find(const cv::Mat& image, float minValue, float maxValue, int *channels, int dim) {	99	cv::Mat find(const cv::Mat& image, float minValue, float maxValue, int *channels, int dim) {
100		100
101	cv::Mat result;	101	cv::Mat result;
102		102
103	hranges[0]= minValue;	103	hranges[0]= minValue;
104	hranges[1]= maxValue;	104	hranges[1]= maxValue;
105		105
106	for (int i=0; i<dim; i++)	106	for (int i=0; i<dim; i++)
107	this->channels[i]= channels[i];	107	this->channels[i]= channels[i];
108		108
109	if (isSparse) { // call the right function based on histogram type	109	if (isSparse) { // call the right function based on histogram type
110		110
111	cv::calcBackProject(&image,	111	cv::calcBackProject(&image,
112	1, // we only use one image at a time	112	1, // we only use one image at a time
113	channels, // vector specifying what histogram dimensions belong to what image channels	113	channels, // vector specifying what histogram dimensions belong to what image channels
114	shistogram, // the histogram we are using	114	shistogram, // the histogram we are using
115	result, // the resulting back projection image	115	result, // the resulting back projection image
116	ranges, // the range of values, for each dimension	116	ranges, // the range of values, for each dimension
117	255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255	117	255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255
118	);	118	);
119		119
120	} else {	120	} else {
121		121
122	cv::calcBackProject(&image,	122	cv::calcBackProject(&image,
123	1, // we only use one image at a time	123	1, // we only use one image at a time
124	channels, // vector specifying what histogram dimensions belong to what image channels	124	channels, // vector specifying what histogram dimensions belong to what image channels
125	histogram, // the histogram we are using	125	histogram, // the histogram we are using
126	result, // the resulting back projection image	126	result, // the resulting back projection image
127	ranges, // the range of values, for each dimension	127	ranges, // the range of values, for each dimension
128	255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255	128	255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255
129	);	129	);
130	}	130	}
131		131
132	// Threshold back projection to obtain a binary image	132	// Threshold back projection to obtain a binary image
133	if (threshold>0.0)	133	if (threshold>0.0)
134	cv::threshold(result, result, 255*threshold, 255, cv::THRESH_BINARY);	134	cv::threshold(result, result, 255*threshold, 255, cv::THRESH_BINARY);
135		135
136	return result;	136	return result;
137	}	137	}
138		138
139	};	139	};
140		140
141		141
142	#endif	142	#endif
143		143

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