数据采集与处理Issue(6)：1187-1195,9.DOI:10.16337/j.1004-9037.2015.06.006
基于自适应最优核时频分布的鸟类识别
Identification of Birds Based on Adaptive Optimal Kernel Time-Frequency Distribution
摘要
Abstract
A bird identification method for the transient characteristics of birdsong signal based on adap‐tive optimal kernel(AOK) time‐frequency distribution identification is proposed .The collected birdsong signal is preprocessed and the spectrum is obtained through the AOK time‐frequency analysis method , Different energy distribution of birds sound signal at different time and different frequency are also ana‐lyzed .Then diagram spectrum is turned into gray image ,the gray level co‐occurrence matrix is calculat‐ed ,image features is extracted as the eigenvalues of birds identification based on gray co‐occurrence ma‐trix parameters at different angles .Finally ,the image texture of the known species is selected to gener‐ate training template and the image texture characteristic parameters of the species for identifying is used to generate the test template ,Template matching is achieved using dynamic time warping (DTW) algo‐rithm .The matching value are compared to find the minimum matching value corresponding templates , therefore the recognition of birds are realized .Finally ,40 kinds of common birds experiments demon‐strate that the overall recognition rate reaches 96% .关键词
自适应最优核时频分布/灰度共生矩阵/图像纹理特征/动态规整Key words
AOK time-frequency distribution/gray level co-occurrence matrix/image texture character-istic parameter/dynamic time warping分类
信息技术与安全科学引用本文复制引用
孙斌,万鹏威,陶达,赵玉晓..基于自适应最优核时频分布的鸟类识别[J].数据采集与处理,2015,(6):1187-1195,9.基金项目
浙江省大学生科研创新活动计划资助项目。 （）
