Description: Peak detection is one of the most important time-domain functions performed in signal monitoring. Peak detection is the process of finding the locations and amplitudes of local maxima and minima in a signal that satisfies certain properties. These properties can be simple or complex. For example, requiring that a peak exceeds a certain threshold value is a simple property. However, requiring that a peak’s shape resembles that of a prototype peak is a complex property. Platform: |
Size: 1024 |
Author:Kirill Sakhnov |
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Description: 红外和可见光的匹配跟踪在军事、遥感等领域有着广泛的应用。针对灰度和图像特征存在比较大差异的红外和可见光图像，本文采用了最大互信息算法，结合形态学梯度和小波分解。互信息算法优点在于不需要对多模图像灰度间的关系做任何假设，不足之处在于它对图像空间信息的忽略而且计算时间较长。本文互信息结合多结构元的形态学梯度检测的图像边缘，可以使得图像匹配精度提高，还能改善局部极值的问题，再利用小波分解对图像进行压缩降低分辨率，可以减少互信息计算量。最后的实验数据表明在配准过程中互信息的计算速度得到了优化，匹配精度得到了提高，实现快速和精确匹配。- Infrared and visible light matching tracking has wide application in military, remote sensing and other fields. There is a relatively large difference for grayscale image features infrared and visible light images, this article uses the maximum mutual information algorithm, combined with morphological gradient and wavelet decomposition. Mutual information algorithm the advantage not need to make any assumptions about the relationship between the multi-mode image gray inadequacies that its image spatial information is ignored and the computation time is longer. This paper mutual information combined with the multi-structural element morphological gradient image edge detection, can make the image matching accuracy is improved, but also to improve the problem of local minima, and then take advantage of the wavelet decomposition to reduce the resolution of the image is compressed, can reduce the amount of mutual information calculated . Finally, the experimental data show that the mutual Platform: |
Size: 280576 |
Author:simon lee |
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Description: 本文提出了一种使用形态学梯度重建、距离变换和标记提取蛋白质点相结合进行区域极小值控制的二次分水岭分割方法。同时为了提取出合格蛋白质点，减少伪蛋白质点的影响，定义了一个合格蛋白质点检测规则，并将之作为提取合格蛋白质点的根据。实验结果表明，该算法对各种凝胶图像均能较好的较好的检测出蛋白质点区域，较好地解决了过分割等问题。-This paper presents a reconstruction using morphological gradient, distance transform and marker proteins extracted combining regional minima controlled secondary watershed segmentation method. Meanwhile, in order to extract protein spots qualified to reduce the impact of pseudo-proteins, defines a qualified protein detection rules, and qualified it as extracting protein spots basis. Experimental results show that the algorithm can better variety of gel images better detect protein spots region solves the problem of over-segmentation, Platform: |
Size: 6986752 |
Author:haoyi |
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Description: Proposed edge detection method based on bee colony algorithm. Utilization Characteristics colony algorithm for image boundary quick search, too
To a group of local optima, and then were local minima to start the search, to find the edge of the image points of the object, all the bees to find the boundary point
The union is the image edges. Simulation results show that the algorithm is feasible and effective.-Proposed edge detection method based on bee colony algorithm. Utilization Characteristics colony algorithm for image boundary quick search, too
To a group of local optima, and then were local minima to start the search, to find the edge of the image points of the object, all the bees to find the boundary point
The union is the image edges. Simulation results show that the algorithm is feasible and effective. Platform: |
Size: 245760 |
Author:王飞 |
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