基于标注词相关度的图像自动标注改善方法

计算机科学 ›› 2015, Vol. 42 ›› Issue (Z6): 238-240.

基于标注词相关度的图像自动标注改善方法

徐功文,廖明海,郑森红,赵洪銮,张志军,赵倩,许春秀

山东协和学院计算机学院济南250107,山东协和学院计算机学院济南250107,山东建筑大学计算机学院济南250101,山东建筑大学计算机学院济南250101,山东建筑大学计算机学院济南250101,山东协和学院计算机学院济南250107,山东协和学院计算机学院济南250107

出版日期:2018-11-14 发布日期:2018-11-14
基金资助:
本文受山东协和学院校内基金(XHXY201431),山东省教育厅项目(J12LN31,J13LN11,J14LN59),2014济南市高校院所自主创新计划项目(201303001,4),山东省自然科学基金青年基金项(ZR2012GQ010)资助

Image Automatic Annotation Based on Correlation of Keywords

XU Gong-wen, LIAO Ming-hai, ZHENG Sen-hong, ZHAO Hong-luan, ZHANG Zhi-jun, ZHAO Qian and XU Chun-xiu

Online:2018-11-14 Published:2018-11-14

摘要/Abstract

摘要： 随着图像数量的增长,图像检索技术已经成为一个活跃的研究领域。图像标记能够有效地组织和处理大量的图片信息并从中检索出用户需要的信息。由于自动图像标记方法根据图像分割后的区域对图像进行标记,准确率不高,因此提出一种结合标注词相关度的图标标注方法。该方法首先根据区域相似度对图像进行标注,然后利用标注词之间的相关性对标注结果进行改善。实验结果证明,该方法能够有效地对图像进行标注。

Abstract: With the growth of the number of images,image retrieval technology has become an active area of research.Image annotation can organize and process large amounts of picture information effectively and retrieve the useful information which the user needs.Image automatic annotation methods tag image based on region after the image segmentation,but the accuracy rate is not high.This paper presented a method to tag images combined the correlation of keywords.Firstly,it tags images according to the similarity of areas.Then it uses the correlation of keywords to improve the results.The experimental results show that this tagging pictures method is effective.

Key words: XU Gong-wen¹ LIAO Ming-hai¹ ZHENG Sen-hong² ZHAO Hong-luan² ZHANG Zhi-jun² ZHAO Qian¹ XU Chun-xiu¹ (School of Computer Shandong Xiehe University,Jinan 250107,China)¹(School of Computer Science and Technology,Shandong Jianzhu University,Jinan 250101,China)²

徐功文,廖明海,郑森红,赵洪銮,张志军,赵倩,许春秀. 基于标注词相关度的图像自动标注改善方法[J]. 计算机科学, 2015, 42(Z6): 238-240. https://doi.org/

XU Gong-wen, LIAO Ming-hai, ZHENG Sen-hong, ZHAO Hong-luan, ZHANG Zhi-jun, ZHAO Qian and XU Chun-xiu. Image Automatic Annotation Based on Correlation of Keywords[J]. Computer Science, 2015, 42(Z6): 238-240. https://doi.org/

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