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基于SLIC融合纹理和直方图的图像显著性检测
引用本文:丁华,王晓东,章联军,陈晓爱,赖佩霞.基于SLIC融合纹理和直方图的图像显著性检测[J].计算机工程与应用,2019,55(3):159-166.
作者姓名:丁华  王晓东  章联军  陈晓爱  赖佩霞
作者单位:宁波大学 信息科学与工程学院,浙江 宁波,315211;宁波大学 信息科学与工程学院,浙江 宁波,315211;宁波大学 信息科学与工程学院,浙江 宁波,315211;宁波大学 信息科学与工程学院,浙江 宁波,315211;宁波大学 信息科学与工程学院,浙江 宁波,315211
基金项目:国家科技支撑计划基金;国家自然科学基金;浙江省自然科学基金
摘    要:针对基于颜色直方图的显著图无法突出边缘轮廓和纹理细节的问题,结合图像的颜色特征、空间位置特征、纹理特征以及直方图,提出了一种基于SLIC融合纹理和直方图的图像显著性检测方法。该方法首先通过SLIC算法对图像进行超像素分割,提取基于颜色和空间位置的显著图;然后分别提取基于颜色直方图的显著图和基于纹理特征的显著图;最后将前两个阶段得到的显著图进行融合得到最终的显著图。此外,通过简单的阈值分割方法得到图像中的显著性目标。实验结果表明,与经典显著性检测算法相比,提出的算法性能明显优于其他算法性能。

关 键 词:SLIC算法  颜色特征  空间位置特征  纹理特征  直方图  显著性检测

Image Saliency Detection Based on SLIC Fusion Texture and Histogram
DING Hua,WANG Xiaodong,ZHANG Lianjun,CHEN Xiao’ai,LAI Peixia.Image Saliency Detection Based on SLIC Fusion Texture and Histogram[J].Computer Engineering and Applications,2019,55(3):159-166.
Authors:DING Hua  WANG Xiaodong  ZHANG Lianjun  CHEN Xiao’ai  LAI Peixia
Affiliation:School of Information Science and Engineering, Ningbo University, Ningbo, Zhejiang 315211, China
Abstract:For the problem that the salient map based on color histogram can’t highlight the edge contour and texture details, a method of image saliency detection based on SLIC fusion of texture and histogram is proposed in this paper, which combines color feature, spatial location feature, texture feature and histogram. Firstly, the SLIC algorithm is used to segment the image and the saliency map based on color and spatial location is extracted. Then, saliency map based on color histogram and saliency map based on texture feature are extracted respectively. Finally, the saliency maps obtained from the first two stages are fused to get the final saliency map. In addition, the saliency target in the image is obtained by a simple threshold segmentation method. The experimental results show that compared with the classical saliency detection algorithms, the performance of the algorithm is much better than that of other algorithms.
Keywords:SLIC algorithm  color feature  spatial location feature  texture feature  histogram  saliency detection  
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