Image process is the process to transmitting images using computer application. We offer projects on image processing Matlab Projects for engineering students. Format of images such as ASTER, Forest Fire, underwater, SAR, satellite, human organ, geospatial and biometric images are used as inputs that can be processed as matlab projects. Edge detection, classification, noise reduction and segmentation are the usual functions of image processing matlab projects.
Noise Reduction in Image Processing Matlab Projects:
Elimination of noises from images is called as noise reduction. There are various noises present in an image.
Types of Noises:
- Speckle noise.
- Quantization Noise.
- Salt and Pepper Noise.
- Periodic Noise.
- Gaussian Noise.
These noises are eliminated with many algorithms and filtering.
Image operations –Types and features:
Many operations are done to change input images into output image. This process is called manipulation. Only digital image can be manipulated. There are three types of operation they are local, point and global.
Local- Has the same input values of neighborhood.
Point- depends on some coordinate input value.
Global- Depends on all values of input image.
Edge Detection in Image Processing Matlab Projects:
Changes of pixel intensity or discontinuities are detected by this method. There are two types of edge detection. They are,
- Gradient based edge detection.
- Laplacian based edge detection.
Gradient edge detection is used to detect images with derivative values. The zero crossing and second order derivatives are detected in laplacian edge detection.
Segmentation in Image Processing Matlab Projects:
The input image is divided into counterparts in the process of segmentation. The most common algorithm used in segmentation is thresholding. Some methods of segmentation are,
- Pixon based method.
- Discontinuity based method.
- Graph based method.
- Hybrid based method.
- Intensity based method.
- Similarity based method.
- Clustering method.
Image with high intensity is segmented by intensity based method. There are two level of thresholding they are local and global thresholding used in Image Processing Matlab Projects. Clusters are formed with attributes in the image. This is segmented using clustering method. To produce high quality image two algorithms is combined in hybrid method.
Projects on soft computing are done to give a fresh new approach on segmentation. This can enable segmentation accuracy and implement medical and satellite imaging.