在一个大的搜索一个小图像 [英] search for a small image in a big one
问题描述
我正在从一个大图像中搜索灰度图像。
I'm working on search a gray-scaled image from a big one.
这是我到目前为止做的,只需从左到右逐个像素搜索从右到上和从上到下,它是灰度的,所以我使用bool作为数据类型(1 ==黑色0 ==白色)。
Here's what I've done so far, simply search pixel by pixel from left to right and top to bottom, it's gray-scaled so I use bool as the data type (1==black 0==white).
#include <iostream>
using namespace std;
template <int WIDTH, int HEIGHT>
struct array {
bool data[WIDTH][HEIGHT];
int width() { return WIDTH; }
int height() { return HEIGHT; }
void random_fill() {
for(int row=0; row<HEIGHT; row++) {
for(int col=0; col<WIDTH; col++) {
data[row][col] = (row*col+col*col) % 3 == 0 ? 1 : 0;
}
}
}
void display() {
cout << "array content:" << endl;
for(int row=0; row<HEIGHT; row++) {
for(int col=0; col<WIDTH; col++) {
cout << data[row][col] << " ";
}
cout << endl;
}
}
void operator=(bool _data[WIDTH][HEIGHT]) {
memcpy(data, _data, WIDTH*HEIGHT);
}
};
struct point {
int x;
int y;
};
// test if a sub-rect of a big_rect matches a small rect
template <typename big_t, typename small_t>
bool rect_match(big_t& big_arr, int x_offset, int y_offset, small_t& small_arr) {
int w = small_arr.width(),
h = small_arr.height();
for(int row=0; row<h; row++) {
for(int col=0; col<w; col++) {
if(big_arr.data[row+y_offset][col+x_offset] != small_arr.data[row][col])
return false;
}
}
return true;
}
// search for a small_rect in a big_rect
template <typename big_t, typename small_t>
point search(big_t& big_arr, small_t& small_arr) {
point pt;
for(int row=0; row<big_arr.height()-small_arr.height(); row++) {
for(int col=0; col<big_arr.width()-small_arr.width(); col++) {
if(rect_match(big_arr, col, row, small_arr)) {
pt.x = col;
pt.y = row;
return pt;
}
}
}
pt.x = pt.y = -1;
return pt;
}
int main() {
array<10, 10> big_arr;
big_arr.random_fill(); // fill the sample image with some "random" color
big_arr.display();
array<3, 3> small_arr;
bool data[3][3] = {{1,0,1},{0,0,1},{0,1,1}};
small_arr = data;
small_arr.display();
point pt = search(big_arr, small_arr);
cout << "pt: (" << pt.x << ", " << pt.y << ")" << endl;
}
我在寻找更好的算法
任何建议?
谢谢。
推荐答案
您可以将较大的图像解释为字符串,以应用字符串搜索算法,如'Boyer-Moore字符串搜索算法'( http://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithm )找到第一行的较小图像。找到该行后,您匹配以下行。
You might interpret the larger image as a string of bytes for applying a string-search algorithm like the 'Boyer–Moore string search algorithm' (http://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithm) to find the first line of the smaller image. After finding that line, you match the following lines.
但是,如果找不到较小的图像(未与较大图像中的字节边界对齐),则必须使用移动的较小图像重复搜索忽略第一个和最后一个字节),直到找到匹配或没有进一步的移位是可信的。
However, if the smaller image is not found (not aligned to a byte boundary in the larger image), you have to repeat the search using a shifted smaller image (temporary ignoring the first and last byte), until you find a match or no further shift is plausible.
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