• Journal of Korea Multimedia Society
• /
• v.15 no.3
• /
• pp.291-298
• /
• 2012

In automatic target recognition(ATR) systems, target extraction techniques are very important because ATR performance depends on segmentation result. So, this paper proposes a multi-sensor image fusion method based on adaptive weights. To incorporate the FLIR image and CCD image, we used information such as the bi-modality, distance and texture. A weight of the FLIR image is derived from the bi-modality and distance measure. For the weight of CCD image, the information that the target's texture is more uniform than the background region is used. The proposed algorithm is applied to many images and its performance is compared with the segmentation result using the single image. Experimental results show that the proposed method has the accurate extraction performance.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.3
• /
• pp.304-310
• /
• 2009

In this paper, target extraction method in FLIR(forward-looking infrared) images based on fuzzy thresholding which used bi-modality and adjacency to determine membership value is proposed. The bi-modality represents how a pixel is classified into a part of target using distribution of pixel values in a local region, and The adjacency is a measure to represent how each pixel is far from the target region. First, membership value is calculated using above two measures, and then fuzzy thresholding is performed to extract the target. To evaluate performance of proposed target extraction method, we compare other segmentation methods using various FLIR tank image. Experimental results show that the proposed algorithm is a good segmentation performance.

• Journal of Korea Multimedia Society
• /
• v.10 no.4
• /
• pp.432-440
• /
• 2007

In this paper, we propose a small target detection algorithm for FLIR image with complex background. First, we compute the motion information of target from the difference between the current frame and the created background image. However, the slow speed of target cause that it has the very low gray level value in the difference image. To improve the gray level value, we perform the local gamma correction for difference image. So, the detection index is computed by using statistical characteristics in the improved image and then we chose the lowest detection index a true target. Experimental results show that the proposed method has significantly the good detection performance.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.5
• /
• pp.665-671
• /
• 2010

This paper propose the DDEGST(divergent-direction-emphasis generalized symmetry transform) which emphasis the symmetry of divergent intensity orientation for effective target extraction in FLIR(forward looking infra-red) images. In the proposed method, we use the exponential function instead of cosine function as a phase weight function in the generalized symmetry transform for effective target extraction in FLIR images which contain a target with higher intensity than a background intensity. To evaluate the performance of the proposed method, we compare the proposed mehtod with conventional GST method in experiments. We prove that the proposed method have better performance in IR images.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.2 s.302
• /
• pp.37-48
• /
• 2005

In this paper, a new object detection method for FLIR images is proposed. The proposed method consists of intensity ranking feature and a classification algerian using the feature. The intensity ranking feature is a representation of an image, from which intensity distribution is regularized. Each object candidate region is classified as object or non-object by the proposed classification algorithm which is based on the intensity ranking similarity between the candidate and object training images. Using the proposed algorithm pixel-wise detection results can be obtained without any additional candidate selection algorithm. In experimental results, it is shown that the proposed ranking feature is appropriate for object detection in a FLIR image and some vehicle detection results in the situation of existing noise, scale variation, and rotation of the objects are presented.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.12B
• /
• pp.2359-2368
• /
• 1999

In this paper we propose a 2D FLIR image-based 3D target recognition system which performs group-to-ground vehicle recognition using the target contour and its degree of reliability extracted from FLIR image. First we extract target from background in FLIR image. Then we define contour points of the extracted target which have high edge gradient magnitude and brightness value as reliable contour point and make reliable contour by grouping all reliable contour points. After that we extract corresponding reliable contours from model contour image and perform comparison between scene and model features which are calculated by DST(discrete sine transform) of reliable contours. Experiment shows that the proposed algorithm work well and even in case of imperfect target extraction it showed better performance then conventional 2D contour-based matching algorithms.

• Proceedings of the IEEK Conference
• /
• 2000.11d
• /
• pp.65-68
• /
• 2000

This paper describes an approach for extracting invariant features using a view-based representation and recognizing an object with a high speed search method in FLIR. In this paper, we use a reformulated eigenspace technique based on robust estimation for extracting features which are robust for outlier such as noise and clutter. After extracting feature, we recognize an object using a partial distance search method for calculating Euclidean distance. The experimental results show that the proposed method achieves the improvement of recognition rate compared with standard PCA.

• 제어로봇시스템학회:학술대회논문집
• /
• 1988.10a
• /
• pp.183-186
• /
• 1988

The problem addressed in this paper is the accurate tracting of a dynamic target using outputs from a forward - looking infrared(FLIR) sensor as measurements. The important variations are 1) the spread of the target intensity pattern in the FLIR image plane, 2) target motion characteristics, and 3) the rms value and both spartial and temporal correlation of the back - ground noise. Based on this insights. design modifications and on - line adaptation copabilities are incorporated to enable this type of filter track highly maneuverable targets such as air-to-air missiles, with spatially distributed and changing image intensity profiles, against, background clutter.

• Proceedings of the Korean Institute of Communication Sciences Conference
• /
• 1992.10a
• /
• pp.358-361
• /
• 1992

• Journal of Korea Multimedia Society
• /
• v.15 no.2
• /
• pp.195-203
• /
• 2012

This paper proposes ground target classification algorithm based on decision fusion and feature extraction method using multi-sensor images. The decisions obtained from the individual classifiers are fused by applying a weighted voting method to improve target recognition rate. For classifying the targets belong to the individual sensors images, features robust to scale and rotation are extracted using the difference of brightness of CM images obtained from CCD image and the boundary similarity and the width ratio between the vehicle body and turret of target in FLIR image. Finally, we verity the performance of proposed ground target classification algorithm and feature extraction method by the experimentation.