融合背景模型及颜色特征的感兴趣目标检测

Salient Object Detection Based by Fusing Background Model and Color Feature

针对传统感兴趣目标检测算法未利用图像自身的先验信息,提出了一种结合图像背景先验信息及颜色特征的感兴趣算法.依据图像边缘区域为一般图像背景的特点,建立了图像背景模型,基于该模型考虑背景区域的差异性,有效避免了目标在图像边缘时造成的漏检现象.通过融合两种显著性特征,得到了最终感兴趣目标.实验结果表明:该算法检测感兴趣目标时,检测准确性较其他主流检测算法提高了10%.

Since the image’s ow n prior information is not used by the traditional salient object detection algorithm ,an algorithm is proposed w hich combines the prior information on the image background with the color features .Based on the features of image edge region being the general image background ,an image background model is built .Because the regional differences in the background are considered in the model ,missing the objects in the edges of the image can be avoided .Then the two significant features are fused to obtain the final goal .Experimental results show that this algorithm increases the detection accuracy by 10% compared with other popular detection algorithms .