Earlier in this chapter, in the Understanding keypoint matching section, we introduced the concept that a keypoint has a descriptor or set of descriptive statistics. Similarly, we can define a custom descriptor for a blob. As our classifier relies on histogram comparison and keypoint matching, let's say that a blob's descriptor consists of a normalized histogram and a matrix of keypoint descriptors. The descriptor object is also a convenient place to put the label. Create a new header file, BlobDescriptor.h, and put the following declaration of a BlobDescriptor class in it:
#ifndef BLOB_DESCRIPTOR_H
#define BLOB_DESCRIPTOR_H
#include <opencv2/core.hpp>
class BlobDescriptor
{
public:
BlobDescriptor(const cv::Mat &normalizedHistogram,
const cv::Mat &keypointDescriptors, uint32_t label);
const cv::Mat &getNormalizedHistogram() const;
const cv::Mat &getKeypointDescriptors() const;
uint32_t getLabel() const...