SIFT局部特征描述算法在图像版权搜索中的应用

Application of SIFT algorithm in the image copyright search

对图像的内容进行准确快速的描述是图像检索技术中研究的重点和难点,传统的图像特征提取方法鲁棒性较差,无法检索出修改过的图像。SIFT特征对局部特征描述能力好,同时对尺度缩放、旋转、平移、仿射变换、光照变化、剪切、降维等修改具有良好的鲁棒性,并且可以应用在多种场景下,但Lowe提出的SIFT算子的提取复杂度和匹配复杂度都非常高。为了应用SIFT对图像的描述能力及其鲁棒性,并提高效率,对SIFT的提取算法进行了修改,消除可以引起边缘响应的部分极值点,消除图像细节丰富的局部过邻近点,消除图像背景中的低对比度点,以降低算法复杂度。同时在特征提取时增加位置限制和幅度限制以降低特征点的数量,从而在匹配效率上也能得到提高。仿真实验表明,该方法在保证图像检索准确度的同时,提高了算法的效率上。

Fast accurate description of image content is the focus and difficulties of image retrieval technology, and the traditional method of robust image feature extraction is poor, unable to retrieve the modified image. Characterization of the ability of local good SIFT algorithm is good at partial characterization description, while the scale scaling, rotation, translation, affine transformations, illumination changes, cut, dimension reduction and other changes, it has good robustness and can be applied in a variety of scenarios, but Lowe proposed the SIFT operator complexity of the extraction and matching complexity is very high. In order to apply SIFI＂ description of the image capacity and its robustness, and efficiency, this extraction of SIFY algorithm has been modified to eliminate some of the response can cause the edge of extreme points, eliminating the image detail is too close to a wealth of local points, to eliminate image in the background of low contrast points to reduce the complexity of the algorithm. Also increased position in the feature extraction limit and rate limit to reduce the number of feature points, resulting in matching efficiency can be improved. Simulation results show that the method to ensure the accuracy of image retrieval at the same time, improve the efficiency of the algorithm.