Ich bin noch ein Anfänger, aber ich möchte ein Zeichenerkennungsprogramm schreiben. Dieses Programm ist noch nicht fertig. Und ich habe viel bearbeitet, daher stimmen die Kommentare möglicherweise nicht genau überein. Ich werde die 8-Konnektivität für die Beschriftung der angeschlossenen Komponenten verwenden.

from PIL import Image
import numpy as np

im = Image.open("D:\\Python26\\PYTHON-PROGRAMME\\bild_schrift.jpg")

w,h = im.size
w = int(w)
h = int(h)

#2D-Array for area
area = []
for x in range(w):
    area.append([])
    for y in range(h):
        area[x].append(2) #number 0 is white, number 1 is black

#2D-Array for letter
letter = []
for x in range(50):
    letter.append([])
    for y in range(50):
        letter[x].append(0)

#2D-Array for label
label = []
for x in range(50):
    label.append([])
    for y in range(50):
        label[x].append(0)

#image to number conversion
pix = im.load()
threshold = 200
for x in range(w):
    for y in range(h):
        aaa = pix[x, y]
        bbb = aaa[0] + aaa[1] + aaa[2] #total value
        if bbb<=threshold:
            area[x][y] = 1
        if bbb>threshold:
            area[x][y] = 0
np.set_printoptions(threshold='nan', linewidth=10)

#matrix transponation
ccc = np.array(area) 
area = ccc.T #better solution?

#find all black pixel and set temporary label numbers
i=1
for x in range(40): # width (later)
    for y in range(40): # heigth (later)
        if area[x][y]==1:
            letter[x][y]=1
            label[x][y]=i
            i += 1

#connected components labeling
for x in range(40): # width (later)
    for y in range(40): # heigth (later)
        if area[x][y]==1:
            label[x][y]=i
            #if pixel has neighbour:
            if area[x][y+1]==1:
                #pixel and neighbour get the lowest label             
                pass # tomorrows work
            if area[x+1][y]==1:
                #pixel and neighbour get the lowest label             
                pass # tomorrows work            
            #should i also compare pixel and left neighbour?

#find width of the letter
#find height of the letter
#find the middle of the letter
#middle = [width/2][height/2] #?
#divide letter into 30 parts --> 5 x 6 array

#model letter
#letter A-Z, a-z, 0-9 (maybe more)

#compare each of the 30 parts of the letter with all model letters
#make a weighting

#print(letter)

im.save("D:\\Python26\\PYTHON-PROGRAMME\\bild2.jpg")
print('done')