Multiple template matching using the expansion filter

Object Tracking System Using Approximate Median Filter, Kalman Filter and Dynamic Template Matching

In this work, we dealt with the tracking of single object in a sequence of frames either from a live camera or a previously saved video. A moving object is detected frame-by-frame with high accuracy and efficiency using Median approximation technique. As soon as the object has been detected, the same is tracked by kalman filter estimation technique along with a more accurate Template Matching a...

Evaluation of Similarity Measures for Template Matching

Image matching is a critical process in various photogrammetry, computer vision and remote sensing applications such as image registration, 3D model reconstruction, change detection, image fusion, pattern recognition, autonomous navigation, and digital elevation model (DEM) generation and orientation. The primary goal of the image matching process is to establish the correspondence between two ...

Object Recognition using Template Matching

Object Recognition is inherently a hard problem in computer vision. Current standard object recognition techniques require small training data sets of images and apply sophisticated algorithms. These methods tend to perform poorly because the small data set does not reflect the true distribution (selection bias). Recently, Torralba et al [1] have proposed to develop a large data set of images (...

A novel approach for template matching by nonorthogonal image expansion

Multiple line-template matching with the EM algorithm

This paper shows how multiple shape hypotheses can be used to recognise complex line patterns using the expectationmaximisation algorithm. The idea underpinning this work is to construct a mixture distribution for an observed configuration of line segments over a space of hypothesised shape models. According to the EM framework each model is represented by a set of maximum likelihood registrati...