Character Feature Extraction Method and Its Effectiveness Evaluation

Present a novel method of character stroke feature extraction based on the histogram of gradient angles. Firstly, produce the gradient angle matrix of the pixels in the character edge by sifting out the gray image using the SOBEL operator. Secondly, set up the character stroke features as sub-vectors of each block matrix using the relationship between the gradient angle matrix and the character strokes. Then, select the block parameters of the gradient angle matrix. Finally, link the sub-vectors as the character feature vector and standardize it. This character feature extraction method integrates the character distributed feature and stroke feature. The recognition accuracy is up to 97%, distinguishing the 12 pixels wide images of license plate character with noise and rotation. This paper also presents a set of character feature vector evaluation to assess the effectiveness of character feature vector.