基于小波特征点的图像检索算法

点匹配技术在基于内容的图像检索中已被广泛使用.提出了一种新的基于小波变换和Barnard算子的彩色特征点检测算法.首先,将彩色图像分解为3个通道并分别对每个通道作小波变换;其次,对一给定的小波系数,通过模极大值可以在高分辨率子图像中找到与之最相关的一个系数,对于第1层小波系数,通过Barnard算子在原始图像数据中查找潜在特征点;最后,通过自适应门限和连续点集约减算法得到最终的特征点.实验表明,该方法提取的特征点具有很强的鲁棒性并能对图像进行有效的表示,可以有效提高图像检所的准确率.

Image retrieval method using wavelet salient points

Point matching techniques have been widely used in content-based image retrieval progress.A new color image salient points detector is proposed based on wavelet transform and the Barnard detector.First,an image is divided into three channels and each channel is decomposed with wavelet transform separately.Second,for a given wavelet coefficient,a corresponding wavelet coefficient is found at a finer scale according to the absolute maximum value.Barnard detector is used when finding potential salient points in the image.Finally,color salient points are extracted by using a self-adaptable threshold and the continuous points set reduction method.Experiments show that this method is robust and the extracted salient points give a satisfying representation of an image.The retrieval performance is also improved effectively.