## MATLAB | Complement Colors in a Binary ImageDigital images with only 0 and 1 are known as binary images. Usually, white and black are the two separate colors these values represent. Typically, in this context, 0 denotes white, and 1 denotes black. Because binary pictures are straightforward and effective at representing specific information, like object masks or outlines, they are frequently employed in image processing and computer vision tasks. - Complementing a binary image entails switching the white and black pixels, effectively reversing the image's colors.
- Dark areas turn into light throughout this procedure, similar to taking a photographic negative when light areas turn into darkness.
## Binary Image Representation:A binary image is one in which every pixel is represented by 0 or 1. A white pixel has a value of 0, commonly represented in an image as a white area. A black pixel, represented by a pixel value of 1, is often displayed as a black area.
- Depending on your desire and convenience, you can utilize the techniques stated in the preceding response, such as arithmetic operations or the imcomplement Function, to perform this color complementation operation in MATLAB or any other image processing software.
- The outcome is a binary image in which the hues of black and white have been switched about or complemented.
You can complement the colors in a binary image by inverting the pixel values in MATLAB.
## Method 1: Using Arithmetic OperationsAs previously mentioned, binary images only have two possible pixel values: 0, which often represents white, and 1, which typically represents black. We carry out a simple arithmetic operation for each pixel in such an image to complete the colors. A more thorough explanation of each stage in this process is provided below: ## Create or Load a Binary ImageStart by creating a binary image programmatically or loading an existing one into MATLAB using the imread Function. You already have a binary image called bwImage for this example. Ensure that the pixels in bwImage have values of 0 and 1, corresponding to the colors white and black, respectively. ## Complement the Colors:It is possible to utilize a straightforward arithmetic technique to complete the colors in a binary image. You deduct the pixel's present value from 1 for each one in the image. This line of MATLAB code flips the colors by subtracting the values of bwImage from 1. Any pixel with a value of 0 (white) will turn into a 1 (black) pixel, and vice versa for any pixel with a value of 1 (black). ## Display the Complemented Image:Use the imshow Function to see the finished image with complementing colors: This command causes the MATLAB figure window to display the bwImageComplement variable as an image. Formerly white areas will appear black in the complemented binary image, and vice versa. ## Save the Complemented Image (Optional):The imwrite Function can be used to store the complementing binary image to a file: The complemented binary picture is saved using this line of code to a file called "complemented_image.png." The file name and format can be changed as necessary. - To get the complemented colors using Method 1, a binary image's pixel values are subtracted from 1.
- Making white pixels black and black pixels white in a binary image in MATLAB is a simple and easy procedure.
Method 2 entails complementing the colors in a binary image using MATLAB's imcomplement Function. This approach is a practical way to avoid using explicit arithmetic operations while getting the same result. ## Method 2 Using the imcomplement FunctionPixel values for binary images in MATLAB are 0 and 1, with 0 commonly denoting white and 1 denoting black. Utilizing the imcomplement Function, perform the following actions to complement the colors of a binary image: ## Create or Load a Binary ImageUse the imread Function in MATLAB to import an existing binary image or generate one programmatically to get started. Assume you already have a binary picture called bwImage. ## Complement the Colors Using imcomplement:Imcomplement, a built-in function in MATLAB, was created specifically to complement photograph colors. - Send your binary picture to the Function as an input to use it:
The complemented binary image bwImageComplement is created by the complement Function using the input binary image bwImage. ## Display the Complemented Image:Use the imshow Function to see the finished image with complementing colors: This command causes the MATLAB figure window to display the bwImageComplement variable as an image. Formerly white areas will appear black in the complemented binary image, and vice versa. ## Save the Complemented Image (Optional):The imwrite Function can be used to store the complementing binary image to a file: saves the complemented binary image to the file "complemented_image.png." The file name and format can be changed as necessary. - To complement the colors in a binary image in MATLAB, Method 2 requires utilizing the complement Function, a practical and simple method.
- It is a quick substitute for manually executing arithmetic operations and was created with this exact use in mind.
- In the binary image, this procedure produces the same outcome as procedure 1, where white pixels turn black and black pixels into white.
The imread Function is first used by the application to read the original binary image. The picture file path you gave was 'zx.jpg.' The actual path to your binary image file should be substituted here.
## Advantages:In MATLAB, complementing an image converts all black (0s) pixels to white (1s) and vice versa. When processing images, this operation can be helpful in several ways. The benefits of complementing binary pictures in MATLAB include the following:
- These procedures can aid in reducing noise, filling in blank spaces, or altering the forms of objects in the image.
- Complementing may be involved in the feature extraction process. Complementing makes calculating features like an object's area, perimeter, and centroid easier.
- Complementing can make differentiating between items and the backdrop simpler during segmentation when working with complicated images.
## Disadvantages:Depending on the exact use case and needs, complementing a binary image in MATLAB by inverting the colors (converting 0s to 1s and 1s to 0s) may have certain drawbacks. Here are a few possible drawbacks:
The built-in functions in MATLAB, including complement for binary image complementation, are performance optimized, handle various data formats, and offer improved error handling. Additionally, MATLAB includes many functions and toolboxes that help streamline your workflow and increase efficiency if you need to carry out more complicated image-processing jobs. |