I was curious how would I move pixel with particular coordinates to another location? Or in other word, change the locations of pixels in the image? And then output the changed image again.
using Images
img_lab = rand(Lab, 10, 10)
For example pixel in (1,1) move to (2,3) and overwrite the existing pixel.
Later I want to implement this idea to real images and to all pixels in the image.
img_lab[2,3] = img_lab[1,1]
The image is just a matrix, and you manipulate its elements the same way.
Related
I've seen a few libraries that pixelate images, some of them even feature non-square shapes such as The Pixelator's circle and diamond shapes.
I'm looking however to make a particular shape, I want a "pixel" that is 19x27 px. Essentially, the image would still look pixelated but it would use tallish rectangle shapes as the pixel base.
Are there any libraries out there that do this, if not, what alterations to existing algorithms/functions would I need to make to accomplish this?
Unless I am not understanding your question, the algorithm you need is quite simple!
Just break your image up into a grid of rectangles the size you want (in this case 19x27). Loop over each section of the grid and take the average color of the pixels inside (you can simply take the average of each channel in RGB independently). Then set all of the pixels contained inside to the average color.
This would give you an image that is the same size as your input. You could of course resize your image first to a more appropriate output size.
You might want to look up convolution matrices.
In a shader, you would use your current pixel location to grab a set of nearby pixels from the original image to render to a pixel in a new buffer image.
It is actually just a slight variation of the Box Blur image processing algorithm except that instead of grabbing from the nearby pixels you would grab by the divisions of the original image relative to the 19x27 divisions of the resulting image.
I am working with RGB images that contain a single object against a monochrome background.
My goal is to isolate the object in the image and resize the image to contain only the object.
I have successfully been able to detect the object by converting the image to a binary image using an appropriate threshold. Then, in order to isolate the object in the original RGB image I use the binary image as a mask with the original RGB image.
maskedImage = bsxfun(#times,originalimage, cast(binaryimage,class(originalimage)));
This leaves me with a image only containing the object surrounded by a black background. This is due to the fact that the binary image mask I used contained the object in white pixels and the background in black pixels and since possess intensity values of 0 the masking process converted all pixels that didn't belong to the object to black pixels. I've attached an example below.
I would now like to draw a bounding box around the object and resize the image to the size of the bounding box, so that I can get rid as much of the surrounding black pixels as possible. Is there any way of doing this? Any help would be appreciated.
Given the segmented image, you want to crop out all of the black pixels and provide the closest bounding box that fully encapsulates the object. That's very simple.
You already have a binary mask that determines what is an object and what's background. You simply need to find the minimum spanning bounding box. You can find the top-left and bottom right corner by obtaining all of the pixel locations that are non-zero in the mask, and finding the minimum and maximum row and column coordinates. You'd then just use these to crop out the segmented image.
As such:
%// Find all non-zero locations in the mask
[row,col] = find(binaryImage);
%// Find the top left corner of the mask
topLeftRow = min(row);
topLeftCol = min(col);
%// Find the bottom right corner of the mask
bottomRightRow = max(row);
bottomRightCol = max(col);
%// Extract the object
extracted = maskedImage(topLeftRow:bottomRightRow, topLeftCol:bottomRightCol, :);
The words of the day are Bounding boxes !
If you want the minimum-area rectangle to crop only the nonzero values, you want the bounding box of your region, then set your phasers to stun and you're all set !
See this Matlab help forum question for more implementation details in Matlab.
I am using http://imageresizing.net/ tools to create an editor.
The user can crop and rotate, but when they crop first and then rotate they lose the correct crop coords because the image coords have changed
for example, given a 100x100 image with a crop of the top left 50x50 pixels would then get rotated clockwise and now shows the crop as the original bottom left 50x50 pixels of the source image.
another example with images:
step one crop:
step two rotate:
coords haven't changed, but now it is no longer the proper crop area
does anyone know of a way to have the crop be relative to the original instead of the origin point?
Are you building something like StudioJS?
StudioJS uses ImageResizer.js to manage the command string and translate co-ordinates.
Consider a workflow where your user crops, rotates, and then re-crops the image. To preserve the original crop you will need to translate the coordinates in javascript. ImageResizer.js can do this.
Is there any way of labeling plots with images. For example, when I use the following:
plot(Y(:,1),Y(:,2),'o','LineWidth',2);
gname(names)
I can label each dot in a plot with a name. Is there any way to insert images instead of names?
It is possible, but not as convenient as gname by far. You can use the low-level version of image to insert images in your plot at arbitrary positions. Here's a simple example which puts the "Mandrill" image that comes with Matlab with its upper left corner pixel at the position (pi/2, 0):
% example plot
x = linspace(0, 2*pi, 100);
plot(x, cos(x))
% insert image
load mandrill
colormap(map)
image('CData', X, 'XData', [pi/2, pi/2 + 0.5], 'YData', [0, -0.3])
The result looks like this:
Problems with this approach:
There is no interactive point-and-click facility, you have to explicitly insert and position the image labels programmatically, or program such a point-and-click facility yourself. ginput might help doing so.
A figure window can only have one associated color map. That means if you have different images, they either all have to use the same colormap or have to be truecolor images.
Not just the position, but also the display size of the image has to be specified in the call to image, and both are by default specified with respect to the plot's coordinate system. This makes it hard to achieve the correct aspect ratio. You can switch (temporarily) to absolute units using the axes property 'Units' , but then you have to figure out the correct position in e.g. absolute millimeters or inches. Moreover, images are usually indexed with vertical coordinates increasing from top to bottom, while plots usually have vertical coordinates increasing from bottom to top. This is the reason for the negative value -0.3 in the 'YData' property above.
Alternatively, you can insert images each in their own little axes sitting on top of the plot's axes, which makes it easy to get the right orientation and aspect ratio using axis image. You'll still have the problem though to figure out the correct position for the axes.
I want to crop an image from a specific row onwards. Please help me how can I do this. I am a beginner in Matlab.
This page has a lot of great info on dealing with images in matlab.
When you load an image in matlab, it is loaded as a MxNx3 matrix. The third dimension stores the RGB values of each pixel. So to crop an image you simply select just the range of rows and columns you want to keep:
cropped_image = image(RowStart:RowEnd,ColStart:ColEnd,:);
See this: http://www.mathworks.com/help/techdoc/creating_plots/f9-47085.html
There is a graph editor icon in the screen where you see your graph, it should look like this:
Press it, you will get a big graph editor, now try pressing on the graph or one of the functions, in the lower right part you can set ranges, this will crop the image.
You can use imcrop function in Matlab
CropIm = imcrop(I, rectangle);
rectangle is a four-element position vector [xmin ymin width height] which indicates the size and position of the crop rectangle.
Im = imread('test.tif');
Im2 = imcrop(Im,[75 68 130 112]);
imshow(Im), figure, imshow(Im2)