Matlab Based Projects for Mtech students is a service started by us for the students, who feel to perform a ground breaking research as a part of their academic project. Everyone is capable of doing a remarkable research, but someone needs to initiate the fire to achieve that desire. We are here to lend our hands as a supportive and guiding background for students, who feel to reach the pinnacle of success. We have served students from 120+ countries worldwide and have created numerous scholars and top experts. We have created our own separate network with our researcher, which makes us as a knowledge hub for budding students. If you wish to stand high in the midst of others, approach us with your needs.


     Matlab Based Projects for Mtech students offers you a wide collection of innovative and eye catching projects. Generally, students prefer projects in Matlab due to its platform support to explore the field of research. We can guide you in the best way as we know what makes your project valuable and worthy. We are members in top 500+ journals, which make us updated with all latest concepts and techniques. Our experts mine best topic for the postgraduate students according to their domain of interest using their vast knowledge and experience. To make your project worthy, two most important aspects is the algorithm and dataset used. These both are the decisive factor of your project. Let’s have a glance over the datasets and algorithms used in various research fields.

Research areas with algorithms in Matlab:

Artificial Intelligence:

  • Genetic algorithm
  • Particle swarm algorithm
  • Stimulated annealing
  • Ant colonization algorithm
  • Fuzzy logic systems

Machine learning algorithms:

  • Logistic Regression
  • SVM(Support vector machine)
  • Linear regression
  • Decision tree
  • Naïve Bayes
  • K-Means and KNN
  • Random forest algorithm

Pattern recognition and computer vision:

  • Supervised learning algorithm(SVM, HOG feature extraction )
  • Unsupervised method algorithm(K-mean clustering, Gaussian mixture model, Markov model)

Image processing:

  • Edge detection (Sobel, canny etc)
  • Thresholding(Otsu’s method)
  • Segmentation(Clustering algorithm-k-means, watershed segmentation etc)
  • Classification(ANN, decision tree, SVM etc)
  • Image denoising (Mean and median filters, adaptive filters etc)

Neural networks:

  • Back propagation algorithm
  • Fuzzy K-means algorithm
  • Resilient back propagation algorithm
  • LMS algorithm
  • Genetic algorithms etc

Datasets used in Matlab (2D and 3D):

  • Medical Imaging(4D and 5D)
  • CT images
  • MRI images
  • X-ray and ultrasonic
  • SAR and ASTER
  • PET and PET-CT
  • Biometric images-Finger, face and iris
  • Satellite images

     Based on these two aspects, students can enhance their project performance. To get a better understanding about projects, let’s have a glance over few recent topics in Matlab:


  • A new Face and Iris Recognition  method to Exploring the Usefulness of Light Field Cameras for Biometrics
  • An Efficient  Tool for Automated Recovery of Fragmented JPEG Files by using JPGcarve
  • An efficient method Convolutional Neural Networks  for Fingerprint Liveness Detection
  • A novel technology on Information Theory and the IrisCode
  • A new approach Semantics-Based Online Malware Detection, for  Efficient Real-Time Protection Against Malware
  • The efficient Security Analysis and Performance Results  based on Secretly Pruned Convolutional Codes
  • A novel technology for perceptual Visual Security Index Based on Edge and Texture Similarities
  • An effective approach on Game-Theoretic Framework for Optimum Decision Fusion in the Presence of Byzantines
  • A new secure approach A Security Metric for Evaluating the Resilience of Networks Against Zero-Day Attacks  based on Network Diversity
  • A novel technology for Adaptive Steganalysis Based on Embedding Probabilities of Pixels