[1]王 楠 *,伍阳停,朱琦赫,等.面向检索应用的商标显著性检测方法[J].计算机技术与发展,2023,33(11):162-168.[doi:10. 3969 / j. issn. 1673-629X. 2023. 11. 024]
 WANG Nan *,WU Yang-ting,ZHU Qi-he,et al.Trademark Saliency Detection Method for Image Retrieval[J].,2023,33(11):162-168.[doi:10. 3969 / j. issn. 1673-629X. 2023. 11. 024]
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面向检索应用的商标显著性检测方法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
33
期数:
2023年11期
页码:
162-168
栏目:
人工智能
出版日期:
2023-11-10

文章信息/Info

Title:
Trademark Saliency Detection Method for Image Retrieval
文章编号:
1673-629X(2023)11-0162-07
作者:
王 楠12 * 伍阳停2 朱琦赫2 李宝安2 惠 健3 王子健2
1. 北京信息科技大学 网络文化与数字传播北京市重点实验室,北京 100029;
2. 北京信息科技大学 计算机学院,北京 100029;
3. 杭州海康威视数字技术有限公司,浙江 杭州 310000
Author(s):
WANG Nan12 * WU Yang-ting2 ZHU Qi-he2 LI Bao-an2 HUI Jian3 WANG Zi-jian2
1. Beijing Key Laboratory of Network Culture and Digital Communication,Beijing Information Science and Technology University,Beijing 100029,China;
2. School of Computer Science,Beijing Information Science and Technology University,Beijing 100029,China;
3. Hangzhou Hikvision Digital Technology Co. ,Ltd. ,Hangzhou 310000,China
关键词:
商标检索商标显著性显著性检测商标数据集图像搜索目标识别U2 -Net
Keywords:
trademark retrievaltrademark saliencysaliency detectiontrademark datasetimage retrievalobject detectionU2 -Net
分类号:
TP391
DOI:
10. 3969 / j. issn. 1673-629X. 2023. 11. 024
摘要:
商标显著性检测是商标检索的重要前提之一,待申请商标需要商标显著性判断,商标相似或侵权判定也需要对商标显著性特征加以判别。 考虑到商标多由图案组成,该文提出了一套面向商标图像的显著性检测方案。 首先,基于中国商标数据库内的商标图像抽取、加工并制成商标数据集,搭建商标数据库并陆续开源一批商标显著性检测数据集。 基于已有显著性检测框架,开发并评估了多种主流显著性检测算法。 结果表明一种适配商标图像的 U2 -Net 深度模型对商标显著性检测效果较好,综合准确率在 92% 左右,后续还需要深入优化和评测。 最后,提出一个面向相似商标检索的显著性检测服务和特征生成解决方案,并开发了相关搜索系统,为后续工业级应用奠定基础。
Abstract:
Trademark saliency detection is one of the important prerequisites for trademark image retrieval. The trademark should beapplied and registered after the saliency judgment.?
For the determination of trademark similarity or infringement,it is also necessary todistinguish saliency features of trademarks. We propose a trademark image-oriented saliency detection scheme. Firstly,in view of thelack of related datasets,a trademark database was built based on the trademark images which are extracted,processed from the Chinese trademark database. After a further evaluation,an open-source trademark saliency detection dataset is proposed. Based on the currentsaliency detection framework,a variety of mainstream saliency detection algorithms have been developed and evaluated. The results showthat a U2 -Net network adapted to the trademark images has the most out standing performance on the trademark saliency detection,and theoverall accuracy is about 92% . The further model optimization training and evaluation should be later established. Finally,a module integrated with the saliency detection service and the feature generation service for the trademark retrieval is proposed. An image-to-image trademark retrieval system has been developed,which lays a foundation for the subsequent industrial applications.

相似文献/References:

[1]汪慧兰,毛晓辉,杨晶晶,等. 融合小波变换和SIFT特征的商标检索方法[J].计算机技术与发展,2015,25(04):89.
 WANG Hui-lan,MAO Xiao-hui,YANG Jing-jing,et al. Trademark Retrieval Method Combining Wavelet Transform and SIFT Features[J].,2015,25(11):89.

更新日期/Last Update: 2023-11-10