Python實現區域生長法腐蝕變化檢測後圖片上小塊錯誤

畢業設計的方向是變化檢測，但是在兩張圖片都分類進行對比以後，總會有一些小的誤差點，由於是編寫了一整套程序，需要把結果呈現在網頁上，所以爲了美觀，腐蝕掉一些小的分類誤差點。代碼是將小誤差塊的面積小於總面積的0.1，作爲測試。

import numpy as np
import cv2


class Point(object):
    def __init__(self, x, y):
        self.x = x
        self.y = y

    def getX(self):
        return self.x

    def getY(self):
        return self.y


def getGrayDiff(img, currentPoint, tmpPoint):
    return abs(int(img[currentPoint.x, currentPoint.y]) - int(img[tmpPoint.x, tmpPoint.y]))


def selectConnects(p):
    if p != 0:
        connects = [Point(-1, -1), Point(0, -1), Point(1, -1), Point(1, 0), Point(1, 1), \
                    Point(0, 1), Point(-1, 1), Point(-1, 0)]
    else:
        connects = [Point(0, -1), Point(1, 0), Point(0, 1), Point(-1, 0)]
    return connects


def regionGrow(img, seeds, thresh, p=1):
    area = 0
    height = img.shape[0]
    weight = img.shape[1]
    seedMark = np.zeros(img.shape)
    seedList = []
    for seed in seeds:
        seedList.append(seed)
    label = 200
    connects = selectConnects(p)
    while (len(seedList) > 0):
        area=area+1
        currentPoint = seedList.pop(0)
        seedMark[currentPoint.x, currentPoint.y] = label
        #print(seedMark[currentPoint.x, currentPoint.y])
        for i in range(8):
            tmpX = currentPoint.x + connects[i].x
            tmpY = currentPoint.y + connects[i].y
            if tmpX < 0 or tmpY < 0 or tmpX >= height or tmpY >= weight:
                continue
            grayDiff = getGrayDiff(img, currentPoint, Point(tmpX, tmpY))
            if grayDiff < thresh and seedMark[tmpX, tmpY] == 0:
                seedMark[tmpX, tmpY] = label
                seedList.append(Point(tmpX, tmpY))
    print(area)
    print(seedMark)
    if area<(height*weight/10):
        for i in range(0, height):
            for j in range(0, weight):
                if seedMark[i][j] == 200:
                    img[i][j] = 255
                    #print(1)
    if area>(height*weight/10):
        for i in range(0, height):
            for j in range(0, weight):
                if seedMark[i][j] == 200:
                    img[i][j] = 1
                    #print(1)
    return img

#def convert():
img = cv2.imread('test.png', 0)
height = img.shape[0]
weight = img.shape[1]
for i in range(0, height):
    for j in range(0, weight):
        if(img[i][j]==0):
            print(i,j)
            seeds = [Point(i, j)]
            binaryImg = regionGrow(img, seeds, 10)
cv2.imshow(' ', binaryImg)
cv2.waitKey(0)

處理後：