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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 99%, 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.

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Accurately estimating the soil wetting pattern that closely reflects the measured value can improve the water use efficiency for drip irrigation. Ignoring the effect of the initial soil water content on the soil wetting pattern affects the accuracy of the estimated results to a certain extent. This research aimed to develop a soil wetting pattern estimation model for drip irrigation that included four easily measurable parameters (i.e., initial soil water content, saturated hydraulic conductivity, total volume of applied water, and emitter discharge rate) based on dimensional analysis theory. In this study, the wetting front advance data of 12 typical soil textures were obtained in Hydras-2D/3D. The estimated values were then compared with measured or simulated wetting front advance values. For different experiments, the mean absolute error, root mean square error, and mean relative error varied from 2.77 to 4.69 cm, 6.20 to 10.61 cm, and 5.61% to 10.51%, respectively. Compared with the existing models, the proposed model was more consistent between the measured and simulated values. Therefore, the proposed model of this study is efficient and simple, which can help accurately estimate the soil wetting pattern of drip irrigation with a variety of soil textures.