基于VGGNet-16的满族服饰识别研究
Recognition of Manchu Clothing Based on VGGNet-16
金丹 1邹珍2
作者信息
- 1. 沈阳市轻工艺术学校 服装系,沈阳 110031
- 2. 杭州鸿盛启科技有限公司,杭州 311199
- 折叠
摘要
针对满族服饰在识别过程中,特征分类不准确且识别精确度低的问题,以满族旗袍为特征识别标准,优化设计 VGGNet-16 与特征处理,完成对满族旗袍的识别.首先,在 VGGNet-16 框架中,通过图像预处理、模型构建与特征提取,完成对满族旗袍的粗略识别;然后,优化特征处理,筛选纹理特征,完成对训练集的分类与预测;最后,实现准确的服饰识别.通过与基于阈值分割的服饰识别算法、基于改进的 DenseNet-BC 服饰识别算法对比得知,识别精确度分别提高6.35%、7.18%,分类精确度分别提高 6.71%、6.50%.
Abstract
In response to the problem of inaccurate feature classification and low recognition accuracy in the recognition process of Manchu clothing,the Manchu cheongsam was taken as the feature recognition standard,the design of VGGNet-16 and feature processing were optimized,while the recognition of Manchu cheongsam was completed.Firstly,in the VGGNet-16 framework,rough recognition of Manchu cheongsam was achieved through image preprocessing,model construction and feature extraction.Afterwards,feature processing was optimized,texture features were filtered,while the classification and prediction of the training set were completed.The accurate clothing recognition was achieved.By comparing the algorithm with the clothing recognition algorithm based on threshold segmentation and the improved DenseNet-BC clothing recognition algorithm,it was found that the recognition accuracy had been improved by 6.35%and 7.18%,while the classification accuracy had been improved by 6.71%and 6.50%.
关键词
满族服饰/卷积神经网络/特征提取Key words
Manchu clothing/convolutional neural network/feature extraction引用本文复制引用
基金项目
辽宁省职业技术教育学会项目(LZYZXJSYB2109)
出版年
2024
NETL
NSTL
万方数据