Collection of HAAR and LBP cascades designed to recognize various street signs

👨 使用 OpenCV 和 Qt 实现人脸（刷脸）登录

Emotion recognition system based on LBP-TOP.

The program uses HOG and LBP features to detect human in images. First, use the HOG feature only to detect humans. Next, combine the HOG feature with the LBP feature to form an augmented feature (HOG-LBP) to detect human. A Two-Layer Perceptron (feedforward neural network) will be used to classify the input feature vector into human or no-human.

Detect, recognize and verify faces using hybrid features: “deep” features from VGG-net + HoG + LBP. Hybrid Features help increase recognition significantly

Lab Experiments under Lab component of CSE3018 - Content-based Image and Video Retrieval course at Vellore Institute of Technology, Chennai

A module that can extract LBP features (local binary pattern) from 3D images. Can be used for extracting features from medical images.

Texture Segmentation using: Gray-Level Co-occurence Matrix, Leung-Malik (LM) Filter Bank and Schmid (S) Filter Bank and Local Binary Pattern.

Facial Expression Classification and Feature Extraction

Where Is (the) Ball /Ball Recognition with OpenCV

Malaria Detection Project on Malaria Cells

A two-class fingerprint spoof detector that uses Local Binary Patterns (LBP) features along with Support Vector Machines (SVM) to distinguish live fingerprints images from spoof samples.

texture classification with svm using lbp and glcm

Gender Detection Project

Fingerprint-Spoof-Detector

Classifier for MOUSE eyes used in behavioural experiments.

It, shoes? It's a demo project to use both traditional computer vision methods and deep learning to detect and recognize shoes based on shoes7k dataset

A selection of python scripts regarding face morphing generation and detection