指纹图像特征提取MATLAB代码

以下是一个简单的指纹图像特征提取MATLAB代码示例：

% 读取指纹图像
fingerprint = imread('fingerprint.jpg');

% 预处理：去除噪声和平滑化图像
fingerprint = medfilt2(fingerprint, [3 3]);
fingerprint = imsmooth(fingerprint, 'Gaussian', 3);

% 提取指纹纹线
[BW, thresh] = edge(fingerprint, 'Canny');
se = strel('disk', 1);
BW = imdilate(BW, se);
BW = imfill(BW, 'holes');

% 提取指纹特征
minutiae = extractMinutiae(BW);

% 显示指纹图像和提取的特征
figure;
subplot(1,2,1), imshow(fingerprint), title('原始图像');
subplot(1,2,2), imshow(BW), hold on;
plot(minutiae(:,1), minutiae(:,2), 'r*');
title('提取的特征');

其中，`extractMinutiae()` 函数是用于提取指纹特征的自定义函数，其代码如下：

function minutiae = extractMinutiae(BW)
    % 提取指纹特征：细节点和断点
    B = bwboundaries(BW);
    boundary = B{1};
    [x,y] = find(BW);
    in = inpolygon(y,x,boundary(:,2),boundary(:,1));
    ridge_pixels = [x(in) y(in)];
    mask = false(size(BW));
    idx = sub2ind(size(BW), ridge_pixels(:,1), ridge_pixels(:,2));
    mask(idx) = true;
    ridge_len = bwlabel(mask, 8);
    ridge_dir = ridgeLenAndDir(ridge_pixels, ridge_len);
    [ridge_end,ridge_branch] = findMinutiae(ridge_pixels, ridge_dir, ridge_len);
    minutiae = [ridge_end; ridge_branch];
end


function [ridge_end,ridge_branch] = findMinutiae(ridge_pixels, ridge_dir, ridge_len)
    % 查找指纹细节点和断点
    ridge_end = [];
    ridge_branch = [];
    for i = 1:max(ridge_len(:))
        idx = find(ridge_len == i);
        if numel(idx) >= 10   % 满足长度阈值
            [r,c] = ind2sub(size(ridge_len), idx);
            xy = [c r];
            [L, W] = size(xy);
            g = zeros(L,1);
            for j = 1:L
                g(j) = ridge_dir(xy(j,2), xy(j,1));
            end
            s = std(g);
            if s < 0.3   % 满足方向阈值
                if L == 2   % 断点
                    ridge_branch = [ridge_branch; xy];
                elseif L == 1   % 细节点
                    ridge_end = [ridge_end; xy];
                else   % 需要进一步分析
                    [~,idx] = min(pdist2(xy,mean(xy)));
                    xy = circshift(xy,idx-1,1);
                    d = pdist(xy,'euclidean');
                    A = atan2(xy(:,2)-mean(xy(:,2)), xy(:,1)-mean(xy(:,1)));
                    [~,max_idx] = max(d);
                    [~,min_idx] = min(d);
                    if A(min_idx) < A(max_idx)
                        ridge_end = [ridge_end; xy(min_idx,:)];
                        ridge_branch = [ridge_branch; xy(max_idx,:)];
                    else
                        ridge_end = [ridge_end; xy(max_idx,:)];
                        ridge_branch = [ridge_branch; xy(min_idx,:)];
                    end
                end
            end
        end
    end
end


function [ridge_dir] = ridgeLenAndDir(ridge_pixels, ridge_len)
    % 计算指纹纹线长度和方向
    [n,~] = size(ridge_pixels);
    ridge_dir = zeros(size(ridge_len));
    for i = 1:n
        r = ridge_pixels(i,1);
        c = ridge_pixels(i,2);
        len = ridge_len(r,c);
        if len > 0
            if len == 1
                ridge_dir(r,c) = 0;
            else
                idx = find(ridge_len == len);
                [r2, c2] = ind2sub(size(ridge_len), idx);
                xy = [c2 r2];
                d = pdist2(xy, [c r]);
                [~,idx] = min(d);
                ridge_dir(r,c) = atan2(r2(idx)-r, c2(idx)-c);
            end
        end
    end
end

该代码使用Canny边缘检测算法提取指纹纹线，然后使用自定义函数 `findMinutiae()` 查找指纹细节点和断点。最后，将提取的特征点绘制在二值化的指纹图像上。注意：该代码仅供参考，实际应用中可能需要根据实际情况进行调整和优化。