基于注意力机制的苗族服饰图案分割

Miao costume pattern segmentation based on the attention mechanism

针对苗族服饰图案存在色彩差异大、样式及纹理多样性等问题,采用传统的图像分割算法进行苗族服饰图案分割,会使得一些特征空间信息丢失,导致图像分割的效率与精度较低。为此,本文提出一种基于注意力机制的苗族服饰图案分割模型,通过提取图像特征,使模型能够更好地将感兴趣的特征从局部水平关联到全局水平。同时也采用了数据增强策略,增加训练数据以提高模型泛化能力。实验结果表明,本文模型与传统语义分割网络(U-Net)和全卷积神经网络(FCN)模型相比,仅采用不到1/2的训练参数,IoU增长了14.79%和18.21%,Dice系数增长了11.03%和13.95%。因此,本文为苗族服饰图案分割算法研究提供了一种有效可行的方法。

Miao nationality is one of the oldest nationalities in the history of China.Miao costumes are a distinctive and colorful ethnic culture formed in the long historical process.The colorful Miao costume patterns highly summarize the pursuit of the national spirit,and the styles,colors and textures are the unique style characteristics of the costume patterns.Therefore,it is of great academic significance and application value for the digital protection and inheritance of Miao costume culture to efficiently and accurately segment minority costume patterns.At present,some scholars have carried out researches on minority costume images,but most of them are based on fuzzy C-means clustering algorithm and active contour model,and few of them are based on the deep learning algorithm for minority costume image segmentation.The traditional image segmentation algorithm used to segment the Miao costume patterns leads to the loss of some characteristics of spatial information and low efficiency and accuracy of image segmentation.In order to promote the digital protection of minority costume images and the inheritance of ethnic culture,aiming at the problems of large color differences,diversified styles and textures of Miao costume patterns,this paper proposes a Miao costume pattern segmentation model based on the attention mechanism.FCN is used as the main structure,and the feature weight of the input image is adjusted by the attention mechanism to improve the segmentation performance,so that the model can better associate the features of interest from the local level to the global level.Firstly,data enhancement is used to preprocess the image data to improve the generalization ability and robustness of the model and avoid over-fitting.Then,the feature extraction of Miao costume patterns is carried out by using the full convolutional network model fused with attention module(CBAM)to reduce the loss of spatial information,so as to effectively improve the segmentation accuracy of the model and reduce the loss rate.The model has a total of nine network layers and uses convolution,Batch Normalization(BN),CBAM,add,pooling,and concat operations.The convolution operation is used to extract image features and double the number of channels.BN operation is mainly used to normalize the training image to prevent the model from over-fitting.CBAM layers make the model pay more attention to foreground pixels while learning network weights.The add layer increases the amount of information under image features.The pooling operation performs down-sampling operation on the image to reduce the image size by two times,retain the main features while reducing the number of parameters,and improve the model generalization ability.Concat operation is used for skip connection between corresponding feature layers,so that the model can extract more rich feature information.Except Sigmoid activation function for the last convolutional layer,ReLU function is used for other layers.Analyzing the visual characteristics of ethnic costume from the perspective of deep learning and computer vision is not only convenient for researchers to store and retrieve ethnic costume images,but also conducive to the digital protection of ethnic costume images and the inheritance of ethnic culture.Finally,the experimental results on the Miao costume pattern data set show that compared with the traditional U-Net and FCN models,the IoU increases by 14.79%and 18.21%,respectively,and the Dice coefficient increases by 11.03%and 13.95%,respectively using less than half of the training parameters.Therefore,this paper provides an effective and feasible method for the research of Miao costume pattern segmentation algorithm.In the future,in-depth research regarding the mapping relationship between costume style feature points and image feature points after image segmentation will be conducted.On a certain basis,the research results play a role in the development and protection of minority costume culture,and also provide certain reference for minority costume image segmentation algorithm research.