Abstract: In order to reduce the computational burden and maintain the recognition rate of the image local descriptor, a binary projection method for image local descriptor was proposed. The image patch was projected and transformed into a binary string for boosting the performance as well as speeding up the matching speed. The projection matrix was optimized by machine learning method to maintain its recognition rate and robustness. The experimental result indicates that only a 32-bit binary string is needed to perform as well as the state-of-art descriptors and it shows significantly faster matching speed.

Key words: binary string, local feature, descriptor, image matching, feature extraction

摘要： 为了提高图像局部特征算法的计算速率与匹配速度，并保持其准确率，提出了一种局部映射二进制串描述符算法。它通过映射的方法将图像局部区域转化成二进制串，从而提高其计算效率与匹配速度，并通过机器学习的方法寻找最佳映射矩阵，保持其准确率。从实验结果表明，只需32比特的二进制串就可以在准确率上媲美现有的局部描述符算法，并在匹配速度上有较大的优势。

关键词: 二进制串, 局部特征, 描述符, 图像匹配, 特征提取