Color Pencil Drawing Based on Convolutional Neural Network

doi:10.13190/j.jbupt.2019-030

Journal of Beijing University of Posts and Telecommunications ›› 2020, Vol. 43 ›› Issue (1): 129-134.doi: 10.13190/j.jbupt.2019-030

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Color Pencil Drawing Based on Convolutional Neural Network

WANG Xiao-yu, HU Xin-hao, HAN Chang-lin

School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China

Received:2019-02-28 Online:2020-02-28 Published:2020-03-27
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Abstract

Abstract: In order to optimize the single generation result of traditional color pencil drawing algorithms, a convolution neural network (CNN) based color pencil drawing generation method is presented. Fractional differentiation is employed to obtain original image contour information, CNN can obtain pencil drawing style, and histogram matching can obtain similar tones. Meanwhile, L-BFGS algorithm is used to synthesize pencil drawing image. This can generate color pencil drawing images of different styles. Experiments show that the images generated can retain more original image detail information, and feature with more flexible and diverse styles.

Key words: fractional differentiation, convolutional neural network, histogram matching, L-BFGS algorithm

CLC Number:

TP391

WANG Xiao-yu, HU Xin-hao, HAN Chang-lin. Color Pencil Drawing Based on Convolutional Neural Network[J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(1): 129-134.

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Color Pencil Drawing Based on Convolutional Neural Network

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