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https://github.com/sarabdevops/imagefilteringsystem

A Java API that can apply one or more kernel filters to an image or a directory of images.
https://github.com/sarabdevops/imagefilteringsystem

intellij java-8

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A Java API that can apply one or more kernel filters to an image or a directory of images.

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README 

        
# Image Filtering System



![](https://github.com/sarabDevOps/ImageFilteringSystem/blob/main/filteringSystemImage.PNG)



#### The project is made for as a part of college work , Module  OOP



### Overview

A Java API that can apply one or more kernel filters to an image or a directory of images.



### Using Kernels to Filter Images



Images are typically stored on a computer in a compressed lossy (JPEG) or lossless (GIF, PNG) 

format. When an image is opened in a graphics application like Photoshop or GIMP, it is 

usually rasterized and converted into a bitmap that uses a 32 bit integer to represent a pixel. 

Each pixel therefore can encode the four ARGB (alpha, red, green, blue) channels using 1 byte, 

creating a range of [0...255] for each channel. The 24 bits of the 3 RGB channels can be used 

to represent 2563

=224=16,777,216 different colours, with the alpha channel controlling the 

transparency of the image. A raw bitmap image of dimensions 800 x 600 pixels will contain a 

total of 480,000 pixels.

Among the many features of a graphics application like Photoshop is the ability to filter an 

image to create some kind of an effect. These effects include edge detection, blurring, 

sharpening and embossing and are created by applying a matrix of values to each pixel in the 

image. The matrix of values is called a convolution matrix, a kernel, or a kernel matrix. A 

convolution is a mathematical operation that blends two functions together



![](https://github.com/sarabDevOps/ImageFilteringSystem/blob/main/Matrix.PNG)



The matrix itself is just a 2D array of numbers that slides across the pixels of the rasterized 

image and is used to compute a new value for each pixel. In the image , the 3 x 3 kernel 

can be used to detect the edges in an image by changing the value of a pixel using the weights 

in the kernel and the immediate surrounding pixels in the image. In the example, the pixel value

89 is converted to 145 by the convolution. The same operation is applied to every pixel in the 

image, including edge pixels at the top, bottom and sides. If the image is in greyscale format,

all pixels are encoded with 1 byte and have a value in the range [0..255] and the convolution 

can be performed by tiling over the image as shown in Fig. 2. If the image is in RGB colour, 

the convolution needs to be applied separately to each colour channel.



### Below shows a set of convolution kernels and their effect on an image

![](https://github.com/sarabDevOps/ImageFilteringSystem/blob/main/inputEffects.PNG)



### Getting Started



Download the zip archive , Navigate to the folder using command promt ,



This command will let you run the project :  java –cp ./oop.jar ie.gmit.sw.Runner.Runner



For detail explanation please -> [Click Me ](https://github.com/sarabDevOps/ImageFilteringSystem/blob/main/imageFilteringSystem/README.pdf)



### Versioning



Version 1



### Authors



[SarabDevOps](https://github.com/sarabDevOps)



## License



This project is licensed under the MIT License - see the [LICENSE.md](https://github.com/sarabDevOps/ImageFilteringSystem/blob/main/LICENSE) file for details