摘要
在对实际采集的大量鼠兔图像进行分析的基础上,完成以下两个工作:建立高原鼠兔图像的目标模型、噪声模型以及不同尺度下的目标模型;建立高原鼠兔图像的高斯马尔可夫随机场背景模型。通过对高斯马尔可夫随机场模型的研究,在3种不同场景的高原鼠兔背景图像中选出3个图像序列,用差分图像计算像素点的累积分布函数,得到的结果与相同均值和方差的高斯分布的累积分布函数一致,从而验证基于高斯马尔可夫随机场景的高原鼠兔背景模型的正确性。高原鼠兔图像目标模型和背景模型的建立为后续的目标检测和识别奠定了基础。
Two works were finished following by analyzing a large number of actual Ochotona curzoniae image.The target model,noise model and the target model under different scales of Ochotona curzoniae image were built;The background model of Ochotona curzoniae image based on Gaussian Markov Random Field was built.Three different scenarios of Ochotona curzoniae image were selected from three image sequence and verified the validity of background model of Ochotona curzoniae image based on Gaussian Markov Random Field by calculating cumulative distribution function(CDF)of the differential value of pixels.The calculated result of CDF is consistent with the CDF of same mean and variance of Gaussian distribution.The establishment of target model and the background model for Ochotona curzoniae is a foundation for the subsequent target detection and recognition.
出处
《中国农机化学报》
2016年第1期204-208,共5页
Journal of Chinese Agricultural Mechanization
基金
国家自然科学基金资助项目(61362034
81360229
61265003)
甘肃省自然科学基金项目(148RJZA020
1310RJY020
1212RJYA033)
关键词
高原鼠兔
高斯马尔可夫随机场
场景模型
Ochotona curzoniae
Gaussian Markov Random Field
model of scene