关键词: 尺度不变特征变换; , 旋转不变局部二值模式; , 图像检索; , 特征提取; , 特征点

Abstract: For the problem of accuracy, realtime performance and illumination in image retrieval and feature extraction with SIFT, a new image features extracting algorithm based on the SIFT was proposed and the Local Binary Patterns (LBP) algorithm. It used the same keypoint detection method as SIFT. After getting the keypoints of the image features, the SIFTLBP descriptor was made up of statistics of gradient information in 16×16 region and rotation invariant LBP value in 9×9 regions around each keypoint, and then building SIFTLBP Feature Descriptor of image in each pixel region as the center. Finally, the extracted features of data were selected based on genetic algorithm, and removed redundant information of feature point to reduce the dimension of the feature vector. Experimental results showed that the proposed algorithm had a good matching result on Visual Image Feature Extraction, it was validated that the algorithm was strongly robust to changes in lighting conditions, and improved the accuracy and the speed of retrieval.

Key words: Scaleinvariant feature transform；Rotation invariant local binary patterns；Image retrieval；Feature extraction, Feature points