How to convert a picture in pure black and white in Rust - image-processing

I want to convert a picture in pure black and white(e.g. no grayscale) using Image crate, the result should be a picture with 0 and 255 RGB values.
Following the docs i've wrote the following:
let img = image::open("photo.jpg").unwrap(); // Load picture
let gray_img = img.grayscale(); // Convert it
// Access a random pixel value
let px = gray_img.get_pixel(0,0);
println!("{:?}", pixel.data); // Print RGB array
The problem here is that, whatever pixel i print, it gives me grayscale value.
So, is there a function to convert an image in pure black and white? Something like Pillow's convert function for Python?

Here's how you can first build a grayscale image then dither it to a Black and White one:
use image::{self, imageops::*};
let img = image::open("cat.jpeg").unwrap();
let mut img = img.grayscale();
let mut img = img.as_mut_luma8().unwrap();
dither(&mut img, &BiLevel);
img.save("cat.png").unwrap(); // this step is optional but convenient for testing
You should of course properly handle errors instead of just doing unwrap.

Related

i wanted to detect objects in a hsv image. but i keep getting an error,,Expected Ptr<cv::UMat> for argument '%s'

i was trying to create a trackbar window and get hsv value of the image by adjusting the trackbar. created a mask and then adjusted the trackbar to detect an object of the hsv image
enter code here
def nothing(x):
pass
cv.namedWindow("Tracking")
cv.createTrackbar("LH","Tracking",0,255,nothing)
cv.createTrackbar("LS","Tracking",0,255,nothing)
cv.createTrackbar("LV","Tracking",0,255,nothing)
cv.createTrackbar("UH","Tracking",255,255,nothing)
cv.createTrackbar("US","Tracking",255,255,nothing)
cv.createTrackbar("UV","Tracking",255,255,nothing)
while True:
frame = cv.imread("C:/Users/acer/Desktop/insects/New folder/ins.jpg")
hsv = cv.cvtColor(frame,cv.COLOR_BGR2HSV)
l_h = cv.getTrackbarPos("LH","Tracking")
l_s = cv.getTrackbarPos("LS","Tracking")
l_v = cv.getTrackbarPos("LV","Tracking")
u_h = cv.getTrackbarPos("UH","Tracking")
u_s = cv.getTrackbarPos("US","Tracking")
u_v = cv.getTrackbarPos("UV","Tracking")
l_b = np.array([l_h,l_s,l_v])
u_b = np.array([u_h,u_s,u_v])
mask = (hsv,l_b,u_b)
res = cv.bitwise_and(frame,frame,mask=mask)
cv.imshow("frame",frame)
cv.imshow("mask",mask)
cv.imshow("res",res)
key = cv.waitKey(1)
if key == 27:
break
cv.destroyAllWindows()
There are a few issues with your code:
1) You have no import statements. You need at least:
import cv2 as cv
import numpy as np
2) Your indentation is incorrect. Your function nothing() should not be indented.
3) You omitted to call inRange(), you need:
mask = cv.inRange(hsv,l_b,u_b)
4) You have scaled the Hue into the range 0..255 when it actually has the range 0..180 when used with uint8 images so that 360 degrees comes out as 180 degrees which is less than the 255 upper limit of uint8.
By the way, it is fairly poor practice to do "loop invariant" stuff inside a loop - I mean the part where you hit the disk every millisecond and re-read the image, re-decode the JPEG and convert it to HSV. All that can be done outside the loop, then inside it, just do a quick memory copy of the HSV image.

Finding largest blob in image

I am having some issues extracting a blob from an image using EmguCV. Everything I see online uses the Contours object, but I guess that was removed from EmguCV3.0? I get an exception every time I try to use it. I haven't found many recent/relevant SO topics that aren't out of date.
Basically, I have a picture of a leaf. The background might be white, green, black, etc. I want to essentially remove the background so that I can perform operations on the leaf without interference with the background. I'm just not sure where I'm going wrong here:
Image<Bgr, Byte> Original = Core.CurrentLeaf.GetImageBGR;
Image<Gray, Byte> imgBinary = Original.Convert<Gray, Byte>();
imgBinary.PyrDown().PyrUp(); // Smoothen a little bit
imgBinary = imgBinary.ThresholdBinaryInv(new Gray(100), new Gray(255)); // Apply inverse suppression
// Now, copy pixels from original image that are black in the mask, to a new Mat. Then scan?
Image<Gray, Byte> imgMask;
imgMask = imgBinary.Copy(imgBinary);
CvInvoke.cvCopy(Original, imgMask, imgBinary);
VectorOfVectorOfPoint contoursDetected = new VectorOfVectorOfPoint();
CvInvoke.FindContours(imgBinary, contoursDetected, null, Emgu.CV.CvEnum.RetrType.List, Emgu.CV.CvEnum.ChainApproxMethod.ChainApproxSimple);
var contoursArray = new List<VectorOfPoint>();
int count = contoursDetected.Size;
for (int i = 0; i < count; i++)
{
using (VectorOfPoint currContour = contoursDetected[i])
{
contoursArray.Add(currContour);
}
}
With this, I get a black image with a tiny bit of white lines. I've racked my brain back and forth and haven't been able to come up with something. Any pointers would be much appreciated!
I think that you need to find which one is the largest area using ContourArea on each one of the contours.
After you find the largest contour you need to fill it (because the contour is just the putline of the blob and not all the pixel in it) using FillPoly and create a mask that as the leaf pixels with value 1 and the everything else with 0.
In the end use the mask to extract the leaf pixels from the original image
I am not so proficient in c# so i attach a code in python with opencv to give you some help.
The resulted image:
Hope this will be helpful enough.
import cv2
import numpy as np
# Read image
Irgb = cv2.imread('leaf.jpg')
R,G,B = cv2.split(Irgb)
# Do some denosiong on the red chnnale (The red channel gave better result than the gray because it is has more contrast
Rfilter = cv2.bilateralFilter(R,25,25,10)
# Threshold image
ret, Ithres = cv2.threshold(Rfilter,0,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
# Find the largest contour and extract it
im, contours, hierarchy = cv2.findContours(Ithres,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE )
maxContour = 0
for contour in contours:
contourSize = cv2.contourArea(contour)
if contourSize > maxContour:
maxContour = contourSize
maxContourData = contour
# Create a mask from the largest contour
mask = np.zeros_like(Ithres)
cv2.fillPoly(mask,[maxContourData],1)
# Use mask to crop data from original image
finalImage = np.zeros_like(Irgb)
finalImage[:,:,0] = np.multiply(R,mask)
finalImage[:,:,1] = np.multiply(G,mask)
finalImage[:,:,2] = np.multiply(B,mask)
cv2.imshow('final',finalImage)
I recommend you look into Otsu thresholding. It gives you a threshold which you can use to divide the image into two classes (background and foreground). using OpenCV's threshold method you can then create a mask if necessary.

ITKImageToCVMat returns white image

I am now doing image registration with ITK library. I read source images with OpenCV, then convert them to ITKImage; after registration, I convert the result to CVMat and use imwrite to store it.
However, ITKOmageToCVMat always gives a white image (show by imshow), and after imwrite, the result isn't stored in the folder. That's so strange...
Below is my code:
cv::Mat img1 = imread(argv[1], IMREAD_GRAYSCALE);
cv::Mat img2 = imread(argv[2], IMREAD_GRAYSCALE);
typedef float PixelType;
const unsigned int Dimension = 2;
typedef itk::Image< PixelType, Dimension > FixedImageType;
typedef itk::Image< PixelType, Dimension > MovingImageType;
typedef itk::OpenCVImageBridge BridgeType;
FixedImageType::Pointer fixedImage = BridgeType::CVMatToITKImage<FixedImageType>(img1);
MovingImageType::Pointer movingImage = BridgeType::CVMatToITKImage<MovingImageType>(img2);
Mat img3 = itk::OpenCVImageBridge::ITKImageToCVMat<MovingImageType>(movingImage);
display("moving image", img3);
string filename3 = "img3";
imwrite(filename3, img3);
Even without registration, just convert an image from CVMat to ITKImage, then convert back, it doesn't work.... Do you have any idea? Thank you :)
Your code is almost fine and it should work but you have to consider 2 things. One is your images' type. When you read an image from hard disk, pixels' values are between 0 and 255 in "uchar" type but you defined the ITK's images in float type { typedef float PixelType; }, so when you convert them back to cv::Mat , they're still float, but their values are more than 1 (0~255) and the maximum value of a float image for "imshow" command, has to be "1", so you just need to divide your image to 255:
imshow("moving image", img3/255);
The second problem is the filename: string filename3 = "img3"; you have to determine the image's format to save, like string filename3 = "img3.bmp";

how to embed a watermark on an image using edge in matlab?

in a school project i would like to do the following step to have a watermaked image in matlab
extract the edges from an image
insert a mark on this edge
reconstruct the image
extract the mark
could some one give me a link to have a good idea how to do it or help me to do that?
thank you in advance
You want to add a watermark to an image? Why not just overlay the whole thing.
if you have an image
img = imread('myimage.jpg')
wm = imread('watermark.jpg')
You can just resize the watermark to the size of the image
wm_rs = imresize(wm, [size(img,1) size(img,2)], 'lanczos2');
img_wm(wm_rs ~= 0) = wm_rs; %This sets non-black pixels to be the watermark. (You'll have to slightly modify this for color images)
If you want to put it on the edges of the image, you can extract them like this
edges = edge(rgb2gray(img),'canny')
Then you can set the pixels where the edges exist to be watermark pixels
img_wm = img;
img_wm(edges ~= 0) = wm_rs(edges~=0);
Instead of direct assignment you can play around with using a mix of the img and wm_rs pixel values if you want transparency.
You'll probably have to adjust some of what I said to color images, but most should be the same.
Here, is a nice and simple example how you can embed watermarks using MATLAB (in the spatial domain): http://imageprocessingblog.com/digital-watermarking/
see example below(R2017b or later release):
% your params
img = imread('printedtext.png');
Transparency = 0.6;
fontColor = [1,1,1]; % RGB,range [0,1]
position = [700,200];
%% add watermark
mask = zeros(size(img),'like',img);
outimg = insertText(mask,position,'china', ...
'BoxOpacity',0,...
'FontSize',200,...
'TextColor', 'white');
bwMask = imbinarize(rgb2gray(outimg));
finalImg = labeloverlay(img,bwMask,...
'Transparency',Transparency,...
'Colormap',fontColor);
imshow(finalImg)

Scripting objects in greyscale images as zero-one array[]

I am trying to script a greyscale object in a captured image as a matrix of 0 1 that represents a block of object pixels (or something like object style scaling), i can imagine the manual processing by looping the object, scaling and writing the matrix according to the grade of color,
however i'm looking for intelligent or open source tools,
.NET are preferred,
[Update, to explain in more details]
The original images are colored, however, i'm converting it into 256 greyscale, then i want to scale it into black or white only, so at the end of the day it's just a black and white picture i want convert it to zero-one matrix,
the following url contains a discussion of how to convert black-white picture to zero-one matrix using a software called imagemagick:
http://studio.imagemagick.org/discourse-server/viewtopic.php?f=1&t=18433
notice the Zero one matrix which demonstrate a dragon face image!, is there any techniques or open source tools that helping me to achieve that?
Something like the following using Emgu OpenCV for .NET would work.
using Emgu.CV;
using Emgu.CV.CvEnum;
using Emgu.CV.Structure;
using System;
using System.Drawing;
using System.IO;
using (Image<Bgr, Byte> img = new Image<Bgr, Byte>("MyImage.jpg"))
{
Matrix<Int32> matrix = new Matrix<Int32>(img.Width, img.Height);
for (int i = 0; i<img.Height;i++)
{
for (int j = 0; j<img.Width;j++)
{
if (img.Data[i,j,2] == 255 &&
img.Data[i,j,1] == 255 &&
img.Data[i,j,0] == 255)
{
matrix.Data[i,j] = 0;
}
else
{
matrix.Data[i,j] = 1;
}
}
}
TextWriter tw = new StreamWriter("output.txt");
for (int i = 0; i<img.Height;i++)
{
for (int j = 0; j<img.Width;j++)
{
tw.Write(matrix.Data[i,j]);
}
tw.Write(tw.NewLine);
}
}
Note that the snippet above loads colour images and creates a matrix with white as 0 and 1 otherwise.
In order to load and work with grayscale images
the Image<Bgr, Byte> becomes an Image<Gray, Byte> and the comparison simplifies to just
if (img.Data[i,j,0] == 255).
Also to do the thresholding (conversion from colour to grayscale to black and white), you can use Otsu's thresholding using the cvThreshold method, using something like :
int threshold = 150;
Image<Bgr, Byte> img = new Image<Bgr, Byte>("MyImage.jpg");
Image<Gray, Single> img2 = img1.Convert<Gray, Single>();
Image<Gray, Single> img3 = new Image<Gray, Single>(img2.Width, img2.Height);
CvInvoke.cvThreshold(img2, img3, threshold, 255, THRESH.CV_THRESH_OTSU);
Other possible tools include
convert from ImageMagick and pnmoraw from netpbm, as mentioned in the URL you linked, with example snippet convert lib/dragon_face.xbm pbm: | pnmnoraw.
Using PIL (Python Image Library) to iterate through image data and the Python IO functions to write the output data
Using System.Drawing.Bitmap specifically the GetPixel method to iterate through the image data, and C# IO functions to write the output data.

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