模式識別課程設(shè)計(jì)

1、模式識別課程設(shè)計(jì)關(guān)于黃綠樹葉的分類問題 成員：李家偉 2015020907010 黃哲 2015020907006 老師：程建 學(xué)生簽字：一、小組分工黃哲：數(shù)據(jù)采集以及特征提取。李家偉：算法編寫設(shè)計(jì)，完成測試編寫報(bào)告。二、特征提取選取黃、綠樹葉各15片，用老師給出的識別算法進(jìn)行特征提取%Extract the feature of the leafclear, close all I = imread('/Users/DrLee/Desktop/kmeans/1.jpg');I = im2double(I);figure, imshow(I)n = input('Ple

2、ase input the number of the sample regions n:');h = input('Please input the width of the sample region h:');Pos = ginput(n);SamNum = size(Pos,1);Region = ;RegionFeatureCum = zeros(2*h+1)*(2*h+1)*3,1);RegionFeature = zeros(2*h+1)*(2*h+1)*3,1);for i = 1:SamNum P = round(Pos(i,:); rectangle

3、('Position', P(1) P(2) 2*h+1 2*h+1); hold on Regioni = I(P(2)-h:P(2)+h,P(1)-h:P(1)+h,:); RegionFeatureCum = RegionFeatureCum + reshape(Regioni,(2*h+1)*(2*h+1)*3,1);endhold offRegionFeature = RegionFeatureCum / SamNum115為綠色樹葉特征，1630為黃色樹葉特征，取n=3；h=1，表示每片葉子取三個區(qū)域，每個區(qū)域的特征為3*3*3維的向量，然后變?yōu)?7*1的列向量，表

4、格如下。綠色：黃色：三、在matlab中用K均值 算法聚類分析利用matlab中的K均值函數(shù)形式其中x為這30個樣本的特征向量。將數(shù)據(jù)列表導(dǎo)入matlab空間，用列表讀取函數(shù)X=xlsread( 總和.numbers,'A2:AD28');Idx,C,sumD,D=kmeans(X,2,dist,'sqEuclidean','rep',4);而后是分類情況的函數(shù)close all;clear all;clc;load(D.mat')for i = 1:15plot(D(i,1),D(i,2),*b'); hold on;plot(D(i+15,1),D(i+15,2),*r');endx1 = sum(D(1:15,1) sum(D(1:15,2);x2 = sum(D(16:30,1) sum(D(16:30,2);x1 = x1./15; x2 = x2./15;plot(x1(1,1),x1(1,2),'or');hold on;plot(x2(1,1),x2(1,2),'ob');hold on;xlabel(x1');ylabel('x2');text(x1(1,1)+0.1,x1(1,2)+0.2 ,第一類