hausdorff distance and it's application to tile images classification

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前段时间有会友发过求瓷砖图片分类的帖子，我看这是一个演示hausdorf距离的好例子，所以就发到这里来了。

hausdorf 距离的介绍请参考如下文献：

[1] D. P. Huttenlocher, G. A. Klanderman, and W. J.

Rucklidge, “Comparing images using the Hausdorff

distance”, IEEE Trans. PAMI, vol. 15, pp. 850-

863, 1993.

[2] Marie-Pierre Dubisson and A.K.Jain. A modified hausdorff distance for

object matching

这里用的是文献[2] modified hausdorff distance.

核心函数：

function d = m_hd(im1, im2)%Effect: compute the modified haussdorff distance between 2 bw image 'im1'%        and 'im2'%inputs:%im1, im2: bw image with the size%outputs:%d: the modified haussdorff distance between 'im1' & 'im2'%Author: Su dongcai at 2012/1/11%Email: suntree4152@gmail.com, qq:272973536%reference:%[1]   D. P. Huttenlocher, G. A. Klanderman, and W.  J. %      Rucklidge, “Comparing  images using the Hausdorff %      distance”,  IEEE  Trans. PAMI,  vol.  15, pp.  850- %      863, 1993.%[2]  Marie-Pierre Dubisson and A.K.Jain. A modified hausdorff distance for%     object matching%0. check inputs:im_sz1 = size(im1); im_sz2 = size(im2);if(sum(abs(im_sz1-im_sz2))~=0)    error('im1 and im2 must with the same size');enddist_im1 = bwdist(im1); dist_im2 = bwdist(im2);pidx_im1 = find(im1); pidx_im2 = find(im2);%eq.(6) in [2]d12 = mean(dist_im1(pidx_im2));d21 = mean(dist_im2(pidx_im1));%eq.(8) in [2]d = max(d12, d21);

结果演示：

splice_alltiles('.\tileImgs', '.\', 'splicedTiles_sort',100, 10, 10, [1:100]);

得到原始未分类图片：

[sort_idx, num_indv] = sortImgs('.\tileImgs', 100, 1.5);

splice_alltiles('.\tileImgs', '.\', 'splicedTiles_sort',100, 10, 10, sort_idx);

得到分类图片：

[local]2[/local]

num_indv =

21 14 12 11 2 2 10 12 4 1 1 3 3 1 3

表示按列优先顺序（从上往下，从左往右），前21块砖为1类，紧接着的14块砖为另一类，以此类推。