Created
January 13, 2018 19:24
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Copy-Move image forgery detection
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| import numpy as np | |
| import cv2 | |
| from scipy.fftpack import fft, dct | |
| import math | |
| import os | |
| def euclidianDistance(a, b): | |
| e = [] | |
| for i in range(0, len(a)): | |
| e.append(a[i] - b[i]) | |
| return math.sqrt(sum([i * i for i in e])) | |
| def block(img): | |
| mboy = 8 | |
| row = len(img) | |
| col = len(img[1]) | |
| vektör = [] | |
| ct = (row - mboy) * (col - mboy) | |
| print(ct) | |
| print("Satir : ", row) | |
| print("Sütun : ", col) | |
| liste = [] | |
| for i in range(0, row - mboy): | |
| for j in range(0, col - mboy): | |
| for a in range(i, i + mboy): | |
| for b in range(j, j + mboy): | |
| vektör.append(img[a, b]) | |
| vektör.append(i) | |
| vektör.append(j) | |
| liste.append(vektör) | |
| vektör = [] | |
| return liste | |
| def eslesme(sirali, esikdegeri): | |
| sonHali = [] | |
| for i in range(0, len(sirali) - 20): | |
| a = i + 20 | |
| for j in range(i + 1, a): | |
| if euclidianDistance(sirali[i, :-2], sirali[j, :-2]) < esikdegeri: | |
| sonHali.append(sirali[i, -2:]) | |
| sonHali.append(sirali[j, -2:]) | |
| return sonHali | |
| def removeimage(img, sonHali): | |
| for i in sonHali: | |
| img[i[0]:i[0] + mboy, i[1]:i[1] + mboy] = 0 | |
| return img | |
| def makeimage(img, imgname): | |
| cv2.imwrite(imgname, img) | |
| def qualityImages(img): | |
| for i in range(90, 101): | |
| imgname = "kum." + str(i) + ".jpg" | |
| cv2.imwrite(imgname, img, [int(cv2.IMWRITE_JPEG_QUALITY), i]) | |
| # 100:150,150:200 | |
| def accuracy(img, ct, uzaklık): | |
| toplamsifir = ct | |
| d1x = [50, 100] | |
| d1y = [100, 150] | |
| d2x = [50, 100] | |
| d2y = [150, 200] | |
| # d1 kesişim r1 | |
| d1 = 0 | |
| print("ct = ", ct) | |
| for i in range(d1x[0], d1x[1]): | |
| for j in range(d1y[0], d1y[1]): | |
| if img[i, j] == 0: | |
| d1 = d1 + 1 | |
| d2 = 0 | |
| for i in range(d2x[0], d2x[1]): | |
| for j in range(d2y[0], d2y[1]): | |
| if img[i, j] == 0: | |
| d2 = d2 + 1 | |
| p = (d2 + d1) / (2 * 50 * 50) | |
| toplam = 0 | |
| for i in range(0, len(img)): | |
| for j in range(0, len(img[i])): | |
| if img[i, j] == 0: | |
| toplam = toplam + 1 | |
| print("toplam:", toplam) | |
| toplam = toplam - toplamsifir | |
| birlesim = (toplam - d1 - d2) + (2 * (50 * 50)) | |
| print(d1, d2) | |
| f = birlesim / (2 * 50 * 50) | |
| print(f) | |
| f = f - p | |
| print(f) | |
| file = open("uzalıklar.txt", 'a') | |
| file.write("p:" + str(p) + "\n" + "F:" + str(f) + "\n") | |
| file.write("\n" + "Uzaklık:" + str(uzaklık) + "\n") | |
| def detectImages(ct): | |
| for i in range(5, 35): | |
| # imgname = "cat." + str(i) + ".jpg" | |
| imgname = "kum.png" | |
| img = cv2.imread(imgname, 0) | |
| print("Making block for " + str(imgname)) | |
| liste = block(img) | |
| liste = np.int_(liste) | |
| print("Lex Sort..") | |
| sirali = liste[np.lexsort((liste[:, 1], liste[:, 0]))] | |
| print("Calculate distance..") | |
| # esikdegeri = esikdegeri - 3 | |
| sonuclar = eslesme(sirali, i) | |
| print("Remove dublicate items..") | |
| img = removeimage(img, sonuclar) | |
| imgname = str("detect.") + str(i) + "." + str(imgname) | |
| makeimage(img, imgname) | |
| accuracy(img, ct, i) | |
| def dublicateImage(img): | |
| dublicate = img[50:100, 100:150] | |
| img[50:100, 150:200] = dublicate | |
| return img | |
| if __name__ == "__main__": | |
| mboy = 8 | |
| ct = 0 | |
| imagename = "kum.png" | |
| img = cv2.imread(imagename, 1) | |
| renksiz = cv2.imread(imagename, 0) | |
| for i in range(0, len(renksiz)): | |
| for j in range(0, len(renksiz[i])): | |
| if renksiz[i, j] == 0: | |
| ct = ct + 1 | |
| img = dublicateImage(img) | |
| qualityImages(img) | |
| detectImages(ct) |
Author
ahmetilgin
commented
Jan 13, 2018
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