Template Matching based Eye Detection in Facial Image

Abstract

Eye detection is a pre-requisite stage for many applications such as human-computer interfaces, iris recognition, driver drowsiness detection, security, and biology systems. In this paper, template based eye detection is described. The template is correlated with different regions of the face image. The region of face which gives maximum correlation with template refers to eye region. The method is simple and easy to implement. The effectiveness of the method is demonstrated in both the cases like open eye as well as closed eye through various simulation results.

Infrared point target detection with improved template matching

“…The classic template matching uses images simply as templates. These templates may be certain objects in a scene or strings of patterns, such as letters forming words in a written text or words or phrases in a spoken text [13] or eyes in face images [14]. However, they are susceptible to variations in scale and light conditions.…”

“…In this experiment phase, our goal is to determine the appropriate kernel and the proper kernel parameters (i.e., the order d in (14) of the polynomial kernel and the width r in (15) of Gaussian kernel) and the eigenvector selection parameter a for (5). Since it is very difficult to determine these parameters simultaneously, a stepwise selection strategy is adopted in our experiments since it is more feasible.…”

Eye Detection Using Composite Cross-Correlation

“…After normalizing the template and face image, the template is compared to all regions of the face image. By calculating the Mean Squared Error (MSE) of correlation between the template and different regions, the region with the lowest MES represents the desired feature (Bhoi and Mohanty, 2010). Facial Feature Extraction Based on Template does not require complex mathematical calculation and prior knowledge about the features geometry but it represent global face structure.…”

“…Dramatically, comparison is calculated by the total differences, Euclidean dimension or crosscorrelation techniques. Bhoi and Mohanti employed cross correlation technique in template match based eye detection (in both cases open eye and close eye) by simple method does not require any complex mathematical calculation and prior knowledge about the eye (Bhoi and Mohanty, 2010). While in the earlier study used template match based approach in order to determine the fatigue drivers but by tracking video sequences and comparing changes on the distance of the eyelids during driving (Dong and Wu, 2005).…”

A Novel Approach to Face Detection Algorithm

“…Nilamani Bhoi et. [6]Al has proposed template based eye detection algorithm in which first the template of eye is taken in gray scale. The normalized eye template is cross correlated with overlapping region of face.…”