A Study on the Effectiveness of Different Patch Size and Shape for Eyes and Mouth Detection

07/10/2010
by   Lim Huey Charn, et al.
0

Template matching is one of the simplest methods used for eyes and mouth detection. However, it can be modified and extended to become a powerful tool. Since the patch itself plays a significant role in optimizing detection performance, a study on the influence of patch size and shape is carried out. The optimum patch size and shape is determined using the proposed method. Usually, template matching is also combined with other methods in order to improve detection accuracy. Thus, in this paper, the effectiveness of two image processing methods i.e. grayscale and Haar wavelet transform, when used with template matching are analyzed.

READ FULL TEXT

page 4

page 5

page 6

page 7

page 8

research
09/10/2014

One-Dimensional Vector based Pattern Matching

Template matching is a basic method in image analysis to extract useful ...
research
03/18/2019

QATM: Quality-Aware Template Matching For Deep Learning

Finding a template in a search image is one of the core problems many co...
research
07/31/2020

Robust Template Matching via Hierarchical Convolutional Features from a Shape Biased CNN

Finding a template in a search image is an important task underlying man...
research
07/14/2014

Optimizing Auto-correlation for Fast Target Search in Large Search Space

In remote sensing image-blurring is induced by many sources such as atmo...
research
04/12/2016

DTM: Deformable Template Matching

A novel template matching algorithm that can incorporate the concept of ...
research
07/18/2017

Fast Screening Algorithm for Rotation and Scale Invariant Template Matching

This paper presents a generic pre-processor for expediting conventional ...
research
09/16/2015

Fast Template Matching by Subsampled Circulant Matrix

Template matching is widely used for many applications in image and sign...

Please sign up or login with your details

Forgot password? Click here to reset