CAJ | 학술논문

反馈日志隐含的图像语义信息有助于图像自动标注，但日志数据中存在的噪声、片面性等问题制约了其作用，故提出基于日志的协同图像自动标注算法。根据日志获取的特点，采用增量关联规则挖掘处理日志信息去除其噪声，利用协同滤波思想扩展图像标注词数量，利用WordNet得到标注词间关系，并结合图像底层特征利用混合概率模型实现图像自动标注。在Corel5K和互联网数据集上的实验表明：该算法降低了日志噪声及片面性所带来的影响，提高了图像自动标注效率和质量。
반궤일지은함적도상어의신식유조우도상자동표주，단일지수거중존재적조성、편면성등문제제약료기작용，고제출기우일지적협동도상자동표주산법。근거일지획취적특점，채용증량관련규칙알굴처리일지신식거제기조성，이용협동려파사상확전도상표주사수량，이용WordNet득도표주사간관계，병결합도상저층특정이용혼합개솔모형실현도상자동표주。재Corel5K화호련망수거집상적실험표명：해산법강저료일지조성급편면성소대래적영향，제고료도상자동표주효솔화질량。
The potential image semantic information in feedback logs helps to improve the quality of image automatic anno-tation, but the noisy and one-sidedness of the log restrict its function. So it proposes a log-based collaborative automatic image annotation algorithm. It uses incremental association rule to mine log messages according to its characteristics to remove the noisy data and expand the amount of image annotation words with the thought of collaborative filtering. Com-bining the relationship of the annotation words from the WordNet and the low-level image features, it can accomplish image automatic annotation with adoption of hybrid probabilistic model. The experimental results based on Corel5K and Internet image set show that the proposed algorithm can reduce the negative effects from noisy and one-sidedness of the log data, and improve the performance and efficiency of the automatic image annotation.