
欧氏距离,即空间中两点的直线距离,设空间中X的坐标为
Y的坐标为
X与Y之间的欧式距离为
uint16_t EuclideanDistance(uint16_t *u16DataA, uint16_t *u16DataB, uint16_t u16Size)
{
uint16_t u16Dist = 0;
int16_t s16Temp = 0;
uint16_t i;
for (i = 0; i < u16Size; i++)
{
s16Temp = ((int16_t)*(u16DataA + i) - ((int16_t)*(u16DataB + i)));
s16Temp = s16Temp * s16Temp;
u16Dist += (uint16_t)s16Temp;
}
u16Dist = (uint16_t)sqrt(u16Dist);
return u16Dist;
}
二、切比雪夫距离(Chebyshev Distance)
1.定义
又称“棋盘距离”,定义为两个点在任意坐标维度上的差值的最大值,设空间中X的坐标为
Y的坐标为
X与Y之间的切比雪夫距离为
uint16_t ChebyshevDistance(uint16_t *u16DataA, uint16_t *u16DataB, uint16_t u16Size)
{
int16_t s16Temp = 0;
uint16_t i;
s16Temp = 0;
uint16_t u16Max = 0;;
for (i = 0; i < u16Size; i++)
{
s16Temp = ((int16_t)*(u16DataA + i) - ((int16_t)*(u16DataB + i)));//
s16Temp = abs(s16Temp);
if (s16Temp > u16Max)
{
u16Max = s16Temp;
}
}
return u16Max;
}
三、曼哈顿距离(Manhattan Distance)
1.定义
又被称为“出租车距离”、“街区距离”,设空间中X的坐标为
Y的坐标为
X与Y之间的曼哈顿距离为
uint16_t ManhattanDistance(uint16_t *u16DataA, uint16_t *u16DataB, uint16_t u16Size)
{
uint16_t u16Dist = 0;
int16_t s16Temp = 0;
uint16_t i;
s16Temp = 0;
for (i = 0; i < u16Size; i++)
{
s16Temp = ((int16_t)*(u16DataA + i) - ((int16_t)*(u16DataB + i)));//
s16Temp = abs(s16Temp);
u16Dist += (uint16_t)s16Temp;
}
return u16Dist;
}
注意:以上各段程序均需包含math.h头文件
#include
各程序均已在STM32F103系列单片机中测试成功。
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