• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.337-350
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• 2006

The characteristics of neighborhood correlation images for change detection were explored at different spatial resolution scales. Bi-temporal QuickBird datasets of Las Vegas, NV were used for the high spatial resolution image analysis, while bi-temporal Landsat $TM/ETM^{+}$ datasets of Suwon, South Korea were used for the mid spatial resolution analysis. The neighborhood correlation images consisting of three variables (correlation, slope, and intercept) were evaluated and compared between the two scales for change detection. The neighborhood correlation images created using the Landsat datasets resulted in somewhat different patterns from those using the QuickBird high spatial resolution imagery due to several reasons such as the impact of mixed pixels. Then, automated binary change detection was also performed using the single and multiple neighborhood correlation image variables for both spatial resolution image scales.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.7
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• pp.587-594
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• 2005

In this paper, a robust correlation-based video tracking is proposed to track a moving object in correlated image sequences. A correlation-based video tracking algorithm seeks to align the incoming target image with the reference target block image, but has critical problems, so called a false-peak problem and a drift phenomenon (correlator walk-off. The false-peak problem is generally caused by highly correlated background pixels with similar intensity of a moving target and the drift phenomenon occurs when tracking errors accumulate from frame to frame because of the nature of the correlation process. At first, the false-peaks problem for the ordinary correlation-based video tracking is investigated using a simple mathematical analysis. And, we will suggest a robust selective-attention correlation measure with a gradient preprocessor combined by a drift removal compensator to overcome the walk-off problem. The drift compensator adaptively controls the template block size according to the target size of interest. The robustness of the proposed method for practical application is demonstrated by simulating two real-image sequences.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.1
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• pp.75-84
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• 1998

To achieve more accurate information from satellite image data, a research on a technique for mixed pixel ex-traction has been produced. The mixed pixels with only two land covers have been experimented. By analyzing canonical vector in canonical correlation classification, the mixed pixels have been classified. The ratio of the two canonical weighted values-the elements of canonical vector have been used as a threshold to discriminate mixed pixels. In case of the classification for the mixed pixels of bridge and water class in TM data before or after the 1st of September, the threshold for the optimal classification of the mixed pixels is 4.0. That is, if the ratio of the two canonical weighted values is less than 4.0, the pixel is a mixed pixel. Also, using the distribution of canonical weighted values, the constitution percentages of land covers within one mixed pixel can be approximately deducted. The accuracy of mixed pixel extraction for experimental area is 90％ and quite acceptable. Conclusively, a technique for mixed pixel extraction by canonical vector analysis is effective.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.8
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• pp.640-646
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• 2003

We presents an edge-based point correlation algorithm for fast and stable visual inspection system. Conventional algorithms based on NGC(normalized gray-level correlation) have to overcome some difficulties in applying automated inspection systems to real factory environment. First of all, NGC algorithms involve highly complex computation and thus require high performance hardware for realtime process. In addition, lighting condition in realistic factory environments is not stable and therefore intensity variation from uncontrolled lights gives many troubles for applying NGC directly as pattern matching algorithm. We propose an algorithm to solve these problems, using thinned and binarized edge data, which are obtained from the original image. A point correlation algorithm with the thinned edges is introduced with image pyramid technique to reduce the computational complexity. Matching edges instead of using original gray-level image pixels overcomes problems in NGC method and pyramid of edges also provides fast and stable processing. All proposed methods are proved by the experiments using real images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.143-150
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• 2009

In this paper, we present a spatial domain error concealment method to recover a lost block in intra-coded frames. The edge directions of the lost block are estimated by the difference values of the border pixels of the accurately received blocks. The lost block is interpolated according to the estimated edge directions. Our algorithm can adaptively recover a lost block according to the estimated edge direction. The distances between pixels are used as weights for interpolation. In spite of the low computational cost, the proposed method outperforms the previous methods in objective and subjective qualities.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.331-337
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• 2017

In this work, we propose an improved form of Zhang's reversible data hiding technique in encrypted image. In the original work, average value of neighboring pixels is used for fluctuation calculation which fails to give good performance. In proposed scheme, to reduce the bit error rate a new function is calculated by summing difference from four neighboring pixels for measuring fluctuation. Moreover, modified calculation of fluctuation function is also proposed where border pixels are considered. The simulation results show that the performance of proposed method outperforms Zhang's and Hong's work. From the results, more information can be sent by using proposed system

• Journal of Mechanical Science and Technology
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• v.14 no.5
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• pp.518-529
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• 2000

A detailed and thorough parametric study of digital image correlation method is presented. A theoretical background and development of the method were introduced and the effects of various parameters on the determination of displacement outputs from the raw original and deformed image information were examined. Use of the normalized correlation coefficient, the use of 20 to 40 pixels for a searching window side, 6 variables searching, bi-cubic spline sub pixel interpolations and the use of coarse-fine search are some of the key choices among the results of parametric studies. The displacement outputs can be further processed with two dimensional curve fitting for the data noise reduction as well as displacement gradient calculation.

• International Journal of Contents
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• v.11 no.4
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• pp.56-69
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• 2015

This paper proposes an efficient image encryption scheme based on quintuple encryption using two chaotic maps. The encryption process is realized with quintuple encryption by calling the encrypt(E) and decrypt(D) functions five times with five different keys in the form EDEEE. The decryption process is accomplished in the reverse direction by invoking the encrypt and decrypt functions in the form DDDED. The keys for the quintuple encryption/decryption processes are generated by using a Tent map. The chaotic values for the encrypt/decrypt operations are generated by using a Gumowski-Mira map. The encrypt function E is composed of three stages: permutation, pixel value rotation and diffusion. The permutation stage scrambles all the rows and columns to chaotically generated positions. This stage reduces the correlation radically among the neighboring pixels. The pixel value rotation stage circularly rotates all the pixels either left or right, and the amount of rotation is based on chaotic values. The last stage performs the diffusion four times by scanning the image in four different directions: Horizontally, Vertically, Principal diagonally and Secondary diagonally. Each of the four diffusion steps performs the diffusion in two directions (forward and backward) with two previously diffused pixels and two chaotic values. This stage ensures the resistance against the differential attacks. The security and performance of the proposed method is investigated thoroughly by using key space, statistical, differential, entropy and performance analysis. The experimental results confirm that the proposed scheme is computationally fast with security intact.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.383-392
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• 2005

Vegetation classes, especially grass and tree classes, are often confused in classification when conventional spectral pattern recognition techniques are used to classify urban areas. This paper reports on a study to improve the classification results by using an automated process of considering height information in separating urban vegetation classes, specifically tree and grass, using three-band, high-spatial resolution, digital aerial imagery. Height information was derived photogrammetrically from stereo pair imagery using cross correlation image matching to estimate differential parallax for vegetation pixels. A threshold value of differential parallax was used to assess whether the original class was correct. The average increase in overall accuracy for three test stereo pairs was $7.8\%$, and detailed examination showed that pixels reclassified as grass improved the overall accuracy more than pixels reclassified as tree. Visual examination and statistical accuracy assessment of four test areas showed improvement in vegetation classification with the increase in accuracy ranging from $3.7\%\;to\;18.1\%$. Vegetation classification can, in fact, be improved by adding height information to the classification procedure.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.701-709
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• 2010

This paper presents an efficient signature recognition method by using the hybrid similarity criterion, which is in inverse proportion to distance and in proportion to correlation between the images. The distance is applied to express the spacial property of image, and the correlation is also applied to express the statistical property. The proposed criterion provides the robust recognition to both the geometrical variations such as position, size, and rotation and the shape variation. The normalized cross-correlation(NCC), which is calculated by considering 4 directions based on the histogram of binary image, is applied to express rapidly and accurately the similarity between the images. The proposed method has been applied to the problem for recognizing the 20 truck images of 288*288 pixels and the 105(3 persons * 35 images) signature images of 256*256 pixels, respectively. The experimental results show that the proposed method has a superior recognition performance that appears the image characters well. Especially, the hybrid criterion of NCC and ordinal distance has a superior recognition performance to the hybrid criterion using city-block or Euclidean distance.