% 利用系统自带的米粒图片rice.png, 对该图片进行预处理后，计算该点中每个米粒的面积和所有米粒的个数，中间用到了求一个点所在的连通域的算法

clear all

clc

close all

I = imread('rice.png');

edI = edge(I, 'canny');

fhI = imfill(edI, 'hole');

se = strel('disk', 4);

opI = imopen(fhI, se);

% opI = ones(100,100);

% opI = im2bw(opI);

figure,imshow(opI);

[row col] = size(opI);

count = 0;

ricearr = zeros(row*col,1);

visited = zeros(size(opI));

% 调用计算连通域函数进行数米粒和计算米粒的面积

for i = 1:row

for j = 1:col

if opI(i,j)&&visited(i,j) == 0

count = count +1;

pt = [i; j];

[c ,domain] = finddomain(opI, pt);

ricearr(count) = c;

for m = 1:c

visited(domain(1,m), domain(2, m)) = 1;

end

end

end

end

disp('米粒的个数为');

disp(count);

disp('每个米粒的面积为');

disp(ricearr(1:count));

% 求一个点所在连通域的算法

function [c, domain] = finddomain(input, pt)

% 输入一幅图像，及图像中的一个点，得到图像中该点所在的连通域和连通域中像素的个数并输出。

% 输入一个白点，将该点周围领域的白点入队列，对队列中的点继续进行查找

[row col] = size(input);

iplus = [-1 -1 0 1 1 1 0 -1];

jplus = [0 1 1 1 0 -1 -1 -1];

visited = zeros(size(input));

stack = zeros(2, row*col);

domain = zeros(2, row*col);

stack(:, 1) = pt;

domain(:, 1) = pt;

visited(pt(1), pt(2)) = 1;

count = 1;

eos = 1;

sos = 1;

while sos ~= eos + 1

m = stack(1, sos);

n = stack(2, sos);

for i = 1: 8 % 寻找邻域中的白点，如果是白点入队列，并标明已访问过。

if m+ iplus(i) > 0 && m + iplus(i) <= row && n + jplus(i) >0 && n + jplus(i) <= col

if input(m + iplus(i), n+ jplus(i)) == 1 && visited(m + iplus(i), n+ jplus(i)) == 0

eos = eos + 1;

stack(:, eos) = [m + iplus(i); n+ jplus(i)];

visited(m + iplus(i), n+ jplus(i)) = 1;

count = count + 1;

domain(:, count) = [m + iplus(i); n + jplus(i)];

end

end

end

sos = sos + 1; % 当邻域内的点都被访问过后，该点出队列，对应指针加1.

end

c = count;