CAJ | 학술논문

在很多场合的应用中,利用图片做数据挖掘之前,有必要区分计算机生成图片和相机拍摄图片.本文针对互联网上的商品图片集(主题为商品的图片,简称商品图).对现有的一些分辨计算机生成图片和相机拍摄图片的方法进行了讨论.分析了各种判别方法在商品图上运行时的局限性,并提出了一种适用于商品图的简单有效的方法.该算法首先从文字图片和图像图片具有不同视角效果的角度对二者进行区分,并将文字图片认定为计算机生成图片;然后时剩余的图像图片的主颜色,颜色多样性等进行综合的判定区分出计算机生成图片.本文在一个拥有40 000张的网上商品图片库上验证了算法的有效性.
재흔다장합적응용중,이용도편주수거알굴지전,유필요구분계산궤생성도편화상궤박섭도편.본문침대호련망상적상품도편집(주제위상품적도편,간칭상품도).대현유적일사분변계산궤생성도편화상궤박섭도편적방법진행료토론.분석료각충판별방법재상품도상운행시적국한성,병제출료일충괄용우상품도적간단유효적방법.해산법수선종문자도편화도상도편구유불동시각효과적각도대이자진행구분,병장문자도편인정위계산궤생성도편;연후시잉여적도상도편적주안색,안색다양성등진행종합적판정구분출계산궤생성도편.본문재일개옹유40 000장적망상상품도편고상험증료산법적유효성.
With the development of online shopping, picture presentation as a shopping guide plays an increasingly important role in the online transaction. In many applications, it is very necessary to distinguish graphics and photographs before data mining. Based on the pictures of goods on the Internet, several ways are discussed to distinguish graphics from photographs, and their limits are analyzed. Then, a simple and effective algorithm is proposed. Firstly, text-images were divided from photographs by human visual habits, and token as graphics. Then, according to the analysis of dominant color and color diversity of the lett images, the part generated by computer was figured out. The result on an online goods picture library including 40 000 pictures demonstrates the effectiveness and applicability of the algorithm.