Matlab中的KNN算法 [英] KNN algo in matlab

问题描述

我正在研究拇指识别系统.我需要实现KNN算法对我的图像进行分类.根据此，它只有2个测量值，通过它可以计算距离以找到最近的邻居，但在我的情况下，我有400张25 X 42的图像，其中200张用于训练，200张用于测试.我正在搜索几个小时，但找不到找到两点之间距离的方法.

I am working on thumb recognition system. I need to implement KNN algorithm to classify my images. according to this, it has only 2 measurements, through which it is calculating the distance to find the nearest neighbour but in my case I have 400 images of 25 X 42, in which 200 are for training and 200 for testing. I am searching for few hours but I am not finding the way to find the distance between the points.

我将第一个200张图像重塑为1 X 1050，并将它们存储在200 X 1050的矩阵trainingData中.类似地，我制作了testingData.

I have reshaped 1st 200 images in to 1 X 1050 and stored them in a matrix trainingData of 200 X 1050. similarly I made testingData.

推荐答案

以下是k近邻分类的示例代码(使用的某些功能需要统计"工具箱):

Here is an illustration code for k-nearest neighbor classification (some functions used require the Statistics toolbox):

%# image size
sz = [25,42];

%# training images
numTrain = 200;
trainData = zeros(numTrain,prod(sz));
for i=1:numTrain
    img = imread( sprintf('train/image_%03d.jpg',i) );
    trainData(i,:) = img(:);
end

%# testing images
numTest = 200;
testData = zeros(numTest,prod(sz));
for i=1:numTest
    img = imread( sprintf('test/image_%03d.jpg',i) );
    testData(i,:) = img(:);
end

%# target class (I'm just using random values. Load your actual values instead)
trainClass = randi([1 5], [numTrain 1]);
testClass = randi([1 5], [numTest 1]);

%# compute pairwise distances between each test instance vs. all training data
D = pdist2(testData, trainData, 'euclidean');
[D,idx] = sort(D, 2, 'ascend');

%# K nearest neighbors
K = 5;
D = D(:,1:K);
idx = idx(:,1:K);

%# majority vote
prediction = mode(trainClass(idx),2);

%# performance (confusion matrix and classification error)
C = confusionmat(testClass, prediction);
err = sum(C(:)) - sum(diag(C))

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