This chapter has demonstrated a general-purpose approach to blob detection and classification. Specifically, we have applied OpenCV functionality to thresholding, morphology, contour analysis, histogram analysis, and keypoint matching.
You have also learned how to load and parse a PLIST file from an application's resource bundle. As Xcode provides a visual editor for PLIST files, they are a convenient way to configure an iOS app. Specifically, in our case, a configuration file lets us separate the classifier's training data from the application code.
We have seen that our detector and classifier work on different kinds of objects, namely beans and coins. We have also seen that the detector and classifier are somewhat robust with respect to variations in lighting, background, blur, reflections, and the presence of neighboring objects.
Finally, we have identified some further reading that may help you take your knowledge of computer vision and mobile app development to the next level...
