Focusing in thermal imagery using morphological gradient operator

Authors:
Myung Geun Chun;Seong G. Kong
Affiliations:
Department of Electronics Engineering, Chungbuk National University, Cheongju, Chungbuk 361-763, South Korea;Imaging and Pattern Recognition Laboratory, Department of Electrical and Computer Engineering, Temple University, Philadelphia, PA 19122, USA
Venue:
Pattern Recognition Letters
Year:
2014

Citing 12
Cited 0

Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Selecting the Optimal Focus Measure for Autofocusing and Depth-From-Focus

IEEE Transactions on Pattern Analysis and Machine Intelligence
Recent advances in visual and infrared face recognition: a review

Computer Vision and Image Understanding
Digital Image Processing (3rd Edition)

Digital Image Processing (3rd Edition)
Evaluation of focus measures in multi-focus image fusion

Pattern Recognition Letters
2D and 3D face recognition: A survey

Pattern Recognition Letters
Face Image Quality Evaluation for ISO/IEC Standards 19794-5 and 29794-5

ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
IR and visible light face recognition

Computer Vision and Image Understanding
Improvements in shape-from-focus for holographic reconstructions with regard to focus operators, neighborhood-size, and height value interpolation

IEEE Transactions on Image Processing
On the focusing of thermal images

Pattern Recognition Letters
An Efficient Algorithm for Focus Measure Computation in Constant Time

IEEE Transactions on Circuits and Systems for Video Technology
Analysis of focus measure operators for shape-from-focus

Pattern Recognition

Quantified Score

Hi-index	0.10

Visualization

Abstract

This paper presents focusing on an object of interest in thermal infrared (IR) imagery using the morphological gradient operator. Most existing focus metrics measure the degree of sharpness on the edge of an object in the field of view, often based on the local gradient operators of pixel brightness intensity. However, such focus measures may fail to find the optimal focusing distance to the object in thermal IR images, where strong edge components of an object do not exist. In particular, when the end goal of image acquisition is object recognition, focusing on an object must retain prominent features of the object for recognition. In this paper, the performances of various focus measures are evaluated in terms of sharpness as well as recognition accuracies for face recognition in thermal IR images. Experiment results show that the morphological gradient operator outperforms conventional gradient operators in terms of autofocusing resolution metric as well as face recognition accuracy.