Digital Image Processing Projects

Matlab ensure user friendly environment in digital image processing projects for  developers. We offer digital image processing projects based on matlab for research scholars contain recognition process, such as tongue, hair pattern, and fingerprint cloth pattern and number plate. We implement satellite image classification, biomedical segmentation and remote sensor image processing from IEEE based papers which play a vital role in digital image processing. We adopt matlab to implement new algorithm or technique to retrieve accurate result. We develop M.Tech thesis for academic technicians with matlab function & GUI to perform analysis task such as computing descriptive analysis, plotting data, Fourier analysis and data fitting.


Human head model realization process using microwave tomography – Digital Image Processing Projects:

We handle head morrhaqic stroke which is a major damage in brain tissue due to lock of blood flow determined by microwave tomography. We implement an efficient algorithm with Gaussian Newton approach to identify stroke based on shape & dielectric properties of human head. We adopt finite difference time domain algorithm to automatically simulate realistic head model. We practice jacobian coefficient to identify similar facts among retrieved dielectric properties.


Retinal based vessel segmentation by feature and ensemble learning – Digital Image Processing Projects::

We segregate ophthalmic and cardio vascular disease such as hyper tension & diabetic retinopathy are identified by retinal blood vessels changes. We propose automatic segmentation & image analysis process lay vital role in retinal vessel segmentation process. We implement supervised methods which combine two superior classifier algorithms such as convolution neural network and random forest method for efficiently segment retinal vessel image. We start with preprocessing to correct all non uniform region in retinal image to enhance vessel contrast. We perform scaling, translation, skewing process based on hierarchy which extracted by convolution neural algorithm.


Detecting diabetic mellitus and retinopathy disease using tongue features  – Digital Image Processing Projects::

We maintain threshold and vector range of normal and abnormal region. We perform segmentation process to separate tongue foreground pixel from background. Then we combine bielliptical deformable template algorithm & contour active filter model to get efficient feature extraction & matching process. By BEDC algorithm, we extract shape, color, texture and input tongue image features. We compute mean and standard deviation & perform matching operation to accurately detect DM & DR disease.


We have developed more than 250+ Digital image Processing Projects for research scholars based on their requirements,