Research on Content-based Automatic Image Annotation Refinement

图像自动标注隶属于计算机视觉、模式识别、信息检索以及机器学习等领域，在学术界和工业界均得到高度的关注，但是由于图像自动标注存在数据集的不平衡性，底层视觉特征与用户高层语义之间的鸿沟等问题，使得图像自动标注仍然面临着许多困难，针对上述情况，本文开展了如下四个方面的研究工作： 1、针对数据库词频分布不平衡问题，提出了一种基于平衡数据库的图像自动标注改善的方法。这个方法主要是通过自动平衡模式找出弱频点，并依据基于外部数据库自动平衡模式对弱频点以下的弱频词，从外部数据库中追加相应数量的图片。通过找到数据库的最佳平衡状态，以及词频的最佳分布使得数据库达到最佳平衡状态，并使得最终标注结果的精确率、召回率...Automatic image annotation is a part of computer vision, pattern recognition, information retrieval and machine learning and other fields, which has a high degree of attention in academia and industry, but because of the image data set of automatic image annotation existing the problem of imbalance, the gap problem between the underlying high-level visual features and high-level user semantic and ...学位：工学硕士院系专业：信息科学与技术学院智能科学与技术系_计算机应用技术学号：3152008115333

Automatic image annotation refinement based on keyword co-occurrence and WordNet

图像自动标注是模式识别与计算机视觉等领域中的重要问题。针对现有图像自动标注模型普遍受到语义鸿沟问题的影响,提出了基于关键词同现的图像自动标注改善方法,该方法利用数据集中标注词间的关联性来改善图像自动标注的结果。此外,针对上述方法不能反映更广义的人的知识以及易受数据库规模影响等问题,提出了基于语义相似的图像自动标注改善方法,通过引入具有大量词汇、包含了人知识的结构化电子词典WOrdnET来计算词汇间的关系并改善图像自动标注结果。实验结果表明,提出的两个图像自动标注改善方法在各项评价指标上相比以往模型均有所提高。Image automatic annotation is a significant and challenging problem in pattern recognition and computer vision areas.At present,most existing image annotation models are influenced by semantic gap problem.This paper proposed a new image automatic annotation refinement method based on co-occurrence to overcome above problem,which used the correlations between keywords in dataset to improve image annotation result.However,above method did not reflect the generalized knowledge of people and easy influenced by the size of dataset.Aiming at above problem,it proposed a new image automatic annotation refinement method based on semantic similarity to overcome above problem.This method used semantic dictionary WordNet to calculate the correlations between keywords and improve the image annotation results.Experimental results conduct on Corel 5K datasets verify the effectiveness of proposed image annotation method.The proposed automatic image annotation model improves the annotation results on all evaluation methods.国家自然科学基金资助项目(60873179;60803078;10871221);高等学校博士学科点专项科研基金资助项目(20090121110032