Image processing is a method of performing operations on an image in order to improve it or obtain useful information from it. Image processing has various applications in fields such as medical, defense, industry, remote sensing, pattern recognition, and video processing, among many others. In this project we will create an application that should identify different objects like rectangle, square and circle etc., based on their features from the input image. Requirements: 1. For this application you should use 4 shapes i.e., square, circle, rectangle and star. 2. Use 10 different sizes for each of the shape. 3. Create 10 images of each of the shape and size using jpeg format in MS paint or any other software. 4. All the images should have equal height and width of 128 X 128 pixels. 5. All the images should have black and white. Black shape with white background. 6. The complete dataset should consist of 400 images. 7. Extract features from the images using different built-in functions of like regionprops() etc. 8. The system should have the capability to test the complete testing set and then generate the accuracy report for all the shapes. 9. The system should also have the capability to test a single image. 10. You should create a proper interface for all these activities. 11. You should use different built-in functions of MATLAB, C++ or Python where applicable. Tools & Technologies: Preferred tool and technology: MATLAB, C++, PYTHON(Any latest version )
Image processing is a method of performing operations on an image in order to improve it or obtain useful information from it. Image processing has various applications in fields such as medical, defense, industry, remote sensing, pattern recognition, and video processing, among many others. In this project we will create an application that should identify different objects like rectangle, square and circle etc., based on their features from the input image.
Requirements:
1. For this application you should use 4 shapes i.e., square, circle, rectangle and star.
2. Use 10 different sizes for each of the shape.
3. Create 10 images of each of the shape and size using jpeg format in MS paint or any other software.
4. All the images should have equal height and width of 128 X 128 pixels.
5. All the images should have black and white. Black shape with white background.
6. The complete dataset should consist of 400 images.
7. Extract features from the images using different built-in functions of like regionprops() etc.
8. The system should have the capability to test the complete testing set and then generate the accuracy report for all the shapes.
9. The system should also have the capability to test a single image.
10. You should create a proper interface for all these activities.
11. You should use different built-in functions of MATLAB, C++ or Python where applicable.
Tools & Technologies:
Preferred tool and technology: MATLAB, C++, PYTHON(Any latest version )
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