使用Python PIL的隐写算法

时间:2017-01-08 13:06:30

标签: python algorithm python-imaging-library steganography

我正在尝试使用Python PIL为B& W图像编码基本的隐写算法。

使用示例图像我可以成功提取其中的隐藏图像,并隐藏其他图像以便随后提取它们。问题在于隐藏文本然后将其解压缩。

代码如下:

from PIL import Image
import matplotlib.pyplot as plt
import scipy.misc as sci
import numpy as np
import array


#CONVERTS IMAGE TO ARRAY OF BINARY 8-BIT NUMBER#
def getImgArray(image):
    w,h = image.size
    out = []
    for x in range(w):
        for y in range(h):
            pixel = image.getpixel((y,x))
            pixel = format(pixel, '08b')
            out.append(pixel)
    return out

def stringByteConverter(data, mode):
    if (mode == "stringToByte"):
        aux = map(ord,data.encode('utf8'))
        aux = [format(char,'08b') for char in aux]
        return aux
    elif (mode == "byteToString"):
        aux = [int(item,2) for item in data]
        aux = "".join(map(chr, aux))
        return aux
    else:
        print("Invalid mode. Use 'stringToByte' or 'byteToString'")

#GETS HIDDEN IMAGE AND RETURNS IT AS BYTE ARRAY REPRESENTING PIXELS#
def getHiddenImage(image):
    buf = ""
    width,height = image.size
    img_aux = []
    for x in range(width):
        for y in range(height):
            if(len(buf)<8):
                pixel = image.getpixel((y,x))
                pixel = format(pixel,'08b')
                buf += pixel[-2:]
            else:
                img_aux.append(buf)
                buf = ""
                pixel = image.getpixel((y,x))
                pixel = format(pixel,'08b')
                buf += pixel[-2:]
    return img_aux

#CONVERT ARRAY OF BYTES TO PNG IMG AND RETURNS PIL IMG OBJECT#
def saveImgArr(ImgArr, size, outputName):
    pixels = np.empty(size)
    iterator = 0
    for i in range(size[0]):
        for j in range(size[1]):
            try:
                pixels[i][j] = int(ImgArr[iterator],2)
                iterator += 1
            except IndexError:
                break

    aux = Image.fromarray(pixels)
    aux = aux.convert("L")
    aux.save(outputName+'.png', 'PNG')
    return pixels

#HIDE IMAGE <src> IN OTHER IMAGE <img>#
def hideImg(src, img, output):
    iterator = 0
    src = src.convert("L")
    srcArr = getImgArray(src)
    imgArr = getImgArray(img)


    for i in range(len(srcArr)):
        buf = []
        buf.append(srcArr[i][:2])
        buf.append(srcArr[i][2:4])
        buf.append(srcArr[i][4:6])
        buf.append(srcArr[i][6:])
        for j in range(4):
            imgArr[iterator] = imgArr[iterator][:-2] + buf[j]
            iterator += 1
    saveImgArr(imgArr,img.size,output)


#HIDE STRING INSIDE IMG#
def hideText(img, string, outputName):
    imgArr = getImgArray(img)
    stringBytes = stringByteConverter(string, "stringToByte")
    iterator = 0
    for i in range(len(string)):
        buf = []
        buf.append(stringBytes[i][:2])
        buf.append(stringBytes[i][2:4])
        buf.append(stringBytes[i][4:6])
        buf.append(stringBytes[i][6:])
        for j in range(4):
            imgArr[iterator] = imgArr[iterator][:-2] + '00'
            imgArr[iterator] = imgArr[iterator][:-2] + buf[j]
            iterator += 1

    print(imgArr[:len(string)*4]) #test print

    saveImgArr(imgArr,img.size,outputName) 

    temp = Image.open(outputName+'.png')
    tempArr = getImgArray(temp)

    print(tempArr[:len(string)*4]) #test print

def getHiddenText(img, msgSize):
    buf = ''
    width,height = img.size
    output = []
    counter = 0
    for x in range(width):
        for y in range(height):
                if(counter < msgSize*4):
                    pixel = img.getpixel((y,x))
                    pixel = format(pixel,'08b')
                    buf += pixel[-2:]
                    counter += 1

    output = stringByteConverter(buf, "byteToString")
    return output

通过在hideText()函数中打印数据数组,我能够获得以下内容:

hideText(lena,'test',"lena_hidden_text")
  

['10100001','10100011','10100001','10100000','10100001',   '10011110','10100001','10100001','10100101','10100011',   '10100000','10011111','10011001','10100011','10011101',   '10011000']

     

['10011110','10100000','10011110','10011101','10011110',   '10011011','10011110','10011110','10100011','10100000',   '10011101','10011100','10010101','10100000','10011001',   '10010100']

hideText()调用获得的第一个向量与它应该完全一样,但在使用saveImgArr()保存图像并使用getImgArr()重新加载后,返回第二个向量,它完全不同。

我不能为我的生活找到问题。由于使用图像提取隐藏数据或隐藏数据,这些功能都非常有效。

我只能猜测我在某种程度上处理错误的文本字节。任何见解都将不胜感激。

1 个答案:

答案 0 :(得分:0)

看起来可疑的一件事是saveImgArr:

aux = Image.fromarray(pixels)
aux = aux.convert("L")

要使用的mode的默认Image.fromarray是从输入的数据类型中推断出来的。

在您的情况下,输入的数据类型是numpy的默认数据类型(浮点数),因此Image将基于浮点数构建。因此,我会预测保存的png图像看起来不正确(只是一个空白图像,因为每个像素都会饱和到1.0)。

要纠正这个问题,您可以提供正确的数据类型来numpy,即更改:

 pixels = np.empty(size)

 pixels = np.empty(size,dtype='uint8')

或通过更改:

将模式显式提供给Image.fromarray
aux = Image.fromarray(pixels)
aux = aux.convert("L")

aux = Image.fromarray(pixels,mode='L')