CAJ | 학술논문

提出一种基于全局特征图像显著性的手绘草图图像检索算法。首先利用图像分割方法获得若干分区，再计算各分区的彩色稀疏直方图，然后利用直方图计算各个分区的颜色对比度。通过剔除对比度低的若干分区从而获取显著目标，将显著目标所在区域按比例分块，保存每个分块的平均灰度和空间关系，作为待搜索的特征数据。搜索过程是将手绘轮廓填充后提取特征数据与保存的特征数据按分块计算灰度的差异，并结合空间权值进行累加。最后将结果排序，值越小则相似度越高。
제출일충기우전국특정도상현저성적수회초도도상검색산법。수선이용도상분할방법획득약간분구，재계산각분구적채색희소직방도，연후이용직방도계산각개분구적안색대비도。통과척제대비도저적약간분구종이획취현저목표，장현저목표소재구역안비례분괴，보존매개분괴적평균회도화공간관계，작위대수색적특정수거。수색과정시장수회륜곽전충후제취특정수거여보존적특정수거안분괴계산회도적차이，병결합공간권치진행루가。최후장결과배서，치월소칙상사도월고。
A hand-drawn sketches image retrieval algorithm based on global saliency detection was proposed.First, the image segmentation method was used to obtain a number of partitions, and then the partition color sparse histogram was calculated, and the histogram was used to calculate each partition color contrast.Saliency target was obtained by eliminating low contrast partitions and was divided into equal blocks .The average gray value of each block and spatial relationships were feature data for searching.Search process was filling hand draw contour and extracting the feature data and comparing the feature data on disk, then the difference was combined with the spatial weights.Finally the results were sorted, and the pictures were similar if the difference was small.This method can extract saliency targets well and can obtain accurate result.