DIP Projects Using MATLAB Research Assistance
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The document discusses digital image processing (DIP) projects using MATLAB. It lists several DIP techniques including image classification, feature extraction, image segmentation, image analysis, image preprocessing, and image enhancement. Image segmentation techniques covered include multi-scale and model-based segmentation, graph partition methods, and color-based segmentation using K-means clustering and region growing. Main applications of DIP discussed are biomedical imaging, remote sensing, automatic visual inspection systems, aerial surveillance, material science, and military applications. Contact information is provided for questions.
DIP Projects Using MATLAB Research Assistance
- 2. DIP Techniques Let we see about of our Advanced techniques used for digital image processing using Matlab listed below, Image Classification Techniques Feature Extraction Image Segmentation Image Analysis Image Preprocessing Image Enhancement
- 3. DIP - Image segmentation The up-to-date concepts of DIP based image segmentation under Matlab projects listed below, Multi scale and model based segmentation Graph partition methods Color based segmentation(K-mean clustering) Region growing and also segmentation Edge detection(Canny method)
- 4. Main Applications of DIP Here, we have listed recent applications research using Matlab projects below, Biomedical Imaging techniques(Heart and lung disease identification, digital mammograms – Imaging) Remote sensing(City planning, flood control, resource mobilization, agricultural production monitoring) Automatic visual inspection system (Incandescent lamp filaments, faulty component identification ) Aerial surveillance (Land and also ocean surveillance) Material science and non destructive evaluation Military applications