This repository is dedicated to the collection of 10 laboratory reports from the "Scene Segmentation and Interpretation" course, a key component of the Master Degree in Vision and Robotics (VIBOT). Each lab focuses on a specific aspect of scene segmentation and interpretation, employing various techniques from edge detection to image restoration.

Coursework for EE569 (Digital Image Processing) at USC for the Spring 2021 Semester

texture classification with svm using lbp and glcm

The Repository has the accumulation of the work done during the summer internship 2021 at Central Electronics Engineering Research Institute. The Research Internship was guided by scientist Dr. Suriya Prakash J at CSIR - CEERI, Chennai. The work comprise of Machine Learning and Deep Learning Techniques for texture classification.

The Repository has the accumulation of the work done during the summer internship 2021 at Central Electronics Engineering Research Institute. The Research Internship was guided by scientist Dr. Suriya Prakash J at CSIR - CEERI, Chennai. The work comprise of Machine Learning and Deep Learning Techniques for texture classification.

Based on a clothing picture and your choices, the app provides you suggestions about your outfit.

Feature Extraction from Image using Local Binary Pattern and Local Derivative Pattern. A contribution to an Open Source Research Project based on building a Python library for feature extraction from images.

Local Binary Patterns Histograms (LBPH) implementation in Go

Texture Classification project created as a part of the individual research project under the guidance of Dr (Prof) Dapeng Wu of the department of Electrical and Computer Engineering in the University of Florida

Texture classification using wavelet CNN in google colab

Small library for Local Binary Pattern Matching

Implementation of fundamental image processing algorithms using MATLAB

TextureClassification using Naive Bayes and GLCM for feature extraction

Gray-Level Co-Occurrence Matrix Feature Extraction

My works for EE 569 - Digital Image Processing - Spring 2018 - Graduate Coursework at USC - Dr. C.-C. Jay Kuo

This repos provides an MATLAB code implementation for the Statistical Approach to Texture Classification from Single Images paper by Varma et. al.

Contains three problems - Texture Classification using k means and Laws filters, Vehicle Classification using SIFT and SURF features and BOWs approach and Edge Detection techniques