CAJ | 학술논문

针对以关键字进行检索分类的图像，首先利用经验设置规则提取初始图像块；对于类中每个备选图像块，寻找所有备选图像块中与其最相似的图像块，并根据梯度方向直方图特征进行聚类，形成特征组；最后，利用图像注册的方式将特征组进行合并，形成商品图像完整的特征。本文以电商图像为例对算法进行了测试，实验结果表明，辨识性特征区域提取的准确率可达70％以上，且与已有方法相比提取特征区域更加完整。
침대이관건자진행검색분류적도상，수선이용경험설치규칙제취초시도상괴；대우류중매개비선도상괴，심조소유비선도상괴중여기최상사적도상괴，병근거제도방향직방도특정진행취류，형성특정조；최후，이용도상주책적방식장특정조진행합병，형성상품도상완정적특정。본문이전상도상위례대산법진행료측시，실험결과표명，변식성특정구역제취적준학솔가체70％이상，차여이유방법상비제취특정구역경가완정。
An image feature identification method is proposed to classify the images according to the key words.Firstly,an empir-ical rule is set to achieve initial patches.Then,the nearest patches of every initial patch are selected.The features of HOG(histo-grams of oriented gradient)are employed to cluster them as the feature group.Finally,the patches are combined to complete fea-ture by the algorithm based on image registering.In the experiments,proposed methods are implemented to analyze E-commerce images.The accuracy of identifiable feature extraction is as high as 70%,and the extracted feature region is more complete than current methods.