A Survey on Breaking Technique of Text-Based CAPTCHA

Table 8

Comparisons of recognition methods.

Recognition methods	Main basis	Typical methods	Advantages	Disadvantages
Recognition method based on template matching	Global property	Traversal search matching algorithm	The program is simple and suitable for standard character verification code.	The required template library is large; it depends on the choice of template matching.
	Local feature	Shape context matching algorithm	The image information is rich, and it is robust to image scaling and affine transformation.	Without rotation invariant.
Recognition method based on character feature	Character structure feature	Algorithm based on character structure feature	Sensitive to the details of characters; strong in distinguishing features.	The distortion is serious when there are noise interferences.
	Character statistical feature	Algorithm based on character statistical feature	Strong robustness against noise interference.	Targeted; application limited.
Recognition method based on machine learning	Template matching	SVM	Strong approximation ability and generalization ability; good adaptability and high accuracy for small sample space; suitable for two kinds of classification.	Not applied to infinite sample space.
		KNN	It is better to avoid the problem of imbalanced samples, which is suitable for overlapping samples of the same class.	Computation is complex; easy to misjudge in the domain with small sample size.
	Traditional method	BPNN	Flexible structure design, suitable for multiclass classification.	Slow convergence rate; depends on parameters.
	Deep learning	CNN	Accepts an input image directly; automatically extracts features; own robustness to displacement, scale, and deformation; high recognition accuracy.	Lack of time dimension; it could not identify using context information.
		RNN	Processes data in time series.	Time gradient may disappear.
		LSTM-RNN	Owns the time memory function; effective to prevent gradient disappear.	Unable to extract feature automatically.