Image processing takes 2D images as input and with various algorithms it processes the output. We offer academic projects based on image processing and all other domains that fall under concepts such as image morphing and pyramids are possible with the help of matlab simulation tool. Other than this animation is also possible with matlab under projects based on Image Processing. Multi spectral images induce certain multimedia concepts. Analyzing and understanding the input images gives an efficient output. Every process involved in image processing concerns with mathematical calculations.
2Dimensional Wavelets: Issues related to the creation of 2D filtering are minimized by 2D wavelets.
Properties of Wavelets:
- Multi resolution wavelet analysis.
- Admissible condition.
In admissible condition many kinds of identifying resolution and reproducing kernel is present. While transforming wavelets no amount of information is lost. A certain condition on wavelet is achieved by property regularity. Signals vary on multi resolution transform multiple frequency bands is decomposed out of these signals. The chief motive of multi resolution signal is to process signals.
Pattern Recognition Projects based on Image Processing:
Objects are analyzing an identical using pattern recognition method. Some application of pattern recognition is as follows:
- Optical character recognition.
- Speech recognition.
- Face recognition.
- Fingerprint recognition.
- Prediction of survival rates for patient’s particular disease.
- Disease categorization.
- Chromosome shape discrimination.
- Texture discrimination.
With the help of pattern recognition and cluster analysis image processing can accept data mining concepts.
Morphological Operations in projects based on Image Processing:
Shape and boundaries of images are changed by morphological operations. The structure element is usually smaller than the image. Chief morphological action is dilation which is layered using structuring element of an image. An image is minimized by erosion. A binary image contains both black and white set of pixels. In the process of binary erosion and dilation other pixels than black pixel are considered as the background. After this opening, closing and shape decomposition is done.
It is an image enhancement process. There are two types of histogram process they are histogram equalization and histogram specification. It involves many processes such as compression, enhancement and segmentation. Mapping is an operation that is done to equalize two histograms. The input image is in an equalized specified histogram.
More advance concept of image processing such as magnetic confinement nuclear fusion is offered by us. Other than this various projects based on image processing are also offered by us.