Article Details


Symbolic Representation Based Approach for Object Identification in Infrared Images

[ Vol. 9 , Issue. 3 ]

Author(s):

Shimoga N. B. Bhushan, Harisha, Arti Pawar and Vidyalakshmi   Pages 235 - 240 ( 6 )

Abstract:


Background: In most of the applications we expect that security cameras or surveillance camera systems should work on an around the clock basis, as also described in various patents. Normal cameras which produce images in visible spectrum are not effective with the absence of natural light. Even though some solutions are there for such problems like morning time natural illumination and night time artificial illumination arrangement for the camera, but these solutions are not practically advisable. Also these solutions have limitations like shadow in the morning or day time. As a result, system may fail in capturing and identifying objects in the dark areas of the current environment. One of the solutions for such problems is usage of Infrared IR cameras instead of visible spectrum cameras.

Methods: This article proposes a novel method of representing infrared images by the use of edgelet features for object recognition application. The proposed technique makes use of interval valued representation for edgelet features of the infrared images. A scheme of identification of the objects based on the proposed features extraction and representation model is also designed.

Results: Experiments conducted to show the effectiveness of the proposed method on publically available IR corpuses viz OSU Thermal Pedestrian Database, Multispectral Image Database and Indoors and Outdoors datasets. Two sets of experimentations are conducted where each set contain three different trails. In the first set of experiments, we have used 40% of the database for training and remaining 60% is used for testing. In the second set of experiments, we have used 60% training and 40% for testing. In each trail we have randomly selected training and testing samples. For the purpose of evaluation of the results, we have calculated precision, recall and f-measure for each trail. The details of the experiments are shown in the Table 1.

Conclusion: This article presents a novel method of representing infrared images by the use of edgelet features for object recognition applications. The proposed technique makes use of interval valued representation for edgelet features for identification of the objects in the infrared images. A method of identification of the objects based on the proposed edgelet features and interval valued representation model is also proposed. Since the features are transformed into interval valued representation, the proposed model drastically reduces the dimension of the feature space which intern reduces the computational time for object recognition in the infrared images. The proposed algorithm is critically analyzed on three publically available corpuses. Further an extensive experimentation is conducted on publically available datasets.

Keywords:

Object recognition, infrared images, interval valued representation.

Affiliation:

Sahyadri College of Engineering and Management, Mangalore, Karnataka



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