• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.355-362
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• 2009

A new intra field deinterlacing algorithm with edge map in the image block is introduced. Conventional deinterlacing methods usually employ edge-based line average algorithm within pixel-by-pixel approach. However, it is sensitive to variation of intensity. To reduce this shortcoming, we proposed edge direction vector computed by edge map, and also its interpolation technique. We first introduce an edge direction vector, which is computed by Sobel mask, so that finer resolution of the edge direction can be acquired. The proposed edge direction vector oriented deinterlacer operates by identifying small pixel variations in five orientations, while weighted averaging to estimate missing pixel. According to the edge direction of the direction vector, we calculate weights on each edge direction. These weight values multiplied by the candidate deinterlaced pixels in order to successively build approximations of the deinterlaced sequence.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.47-52
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• 2003

Change detection and analysis is a powerful application of remote sensing, in that the spectral resolution of multi-band sensors can be used to advantage in monitoring both significant and subtle land cover changes over time. In this study, the LANDSAT TM data was used to detect the change areas affected by flood from a heavy rainfall. The study area is the Nakdong River located in the Korea peninsular. Among the several change detection techniques, change vector analysis(CVA), principle component analysis(PCA) and image difference approach are utilized in this paper. CVA uses any number of spectral bands from multi-date satellite data to produce change image that yield information of the magnitude and direction of differences pixel values. And accuracy assessment was carried out with a change image produced from three techniques. In result, CVA was found to be the most accurate for detecting areas affected by flood. CVA with the overall accuracy and Kappa coefficient of 97.27 percent and 94.45 percent, respectively.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.8-16
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• 2024

Communication with the deaf has always been crucial. Deaf and hard-of-hearing persons can now express their thoughts and opinions to teachers through sign language, which has become a universal language and a very effective tool. This helps to improve their education. This facilitates and simplifies the referral procedure between them and the teachers. There are various bodily movements used in sign language, including those of arms, legs, and face. Pure expressiveness, proximity, and shared interests are examples of nonverbal physical communication that is distinct from gestures that convey a particular message. The meanings of gestures vary depending on your social or cultural background and are quite unique. Sign language prediction recognition is a highly popular and Research is ongoing in this area, and the SVM has shown value. Research in a number of fields where SVMs struggle has encouraged the development of numerous applications, such as SVM for enormous data sets, SVM for multi-classification, and SVM for unbalanced data sets.Without a precise diagnosis of the signs, right control measures cannot be applied when they are needed. One of the methods that is frequently utilized for the identification and categorization of sign languages is image processing. African Buffalo Optimization using Support Vector Machine (ABO+SVM) classification technology is used in this work to help identify and categorize peoples' sign languages. Segmentation by K-means clustering is used to first identify the sign region, after which color and texture features are extracted. The accuracy, sensitivity, Precision, specificity, and F1-score of the proposed system African Buffalo Optimization using Support Vector Machine (ABOSVM) are validated against the existing classifiers SVM, CNN, and PSO+ANN.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.4
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• pp.232-237
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• 2013

This paper presents image database retrieval based on maximum color occurrenceusing Hue, Saturation and Value (HSV) color space. Our system is based on color segmentation. We dividedthe image into n number of areas based on different selected ranges of hue and value, then each area is partitioned into m number of segments based on the number of pixels it contains, after this we calculated the maximumcolor occurrence in each segment and used its HSV value. This is used as a feature vector.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1205-1206
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• 2008

In the conventional floating display system some image distortions might be occurred in the floating image plane, in which a flat screen has been mostly used for providing an adequate input image plane. In this paper, as a new approach to alleviate image distortion problem in a floating display system, a curved screen is suggested by through some computer simulation using an optics design program of Light Tools.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.9
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• pp.1420-1427
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• 1989

A new block matching algorithm that improved the existing block matching algorithm in terms of image quality is proposed in this paper. The subblock of image including the vertical edge of object is subdivided into new two subblocks, and the moving vector found. The result of computer simulation shows on real image that the image quality by the algorithm becomes higher than that of the three step search algorithm by 1.1dB.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.67-73
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• 2015

In a distribution of digital image, there is a serious problem that is the image alteration by a forger. For the problem solution, this paper proposes the forensic decision algorithm of a median filtering (MF) image using the feature vector based on a coefficient of variation (c.v.) of Fourier transform. In the proposed algorithm, we compute Fourier transform (FT) coefficients of row and column line respectively of an image first, then c.v. between neighboring lines is computed. Subsquently, 10 Dim. feature vector is defined for the MF detection. On the experiment of MF detection, the proposed scheme is compared to MFR (Median Filter Residual) and Rhee's MF detection schemes that have the same 10 Dim. feature vector both. As a result, the performance is excellent at Unaltered, JPEG (QF=90), Down scaling (0.9) and Up scaling (1.1) images, and it showed good performance at Gaussian filtering ($3{\times}3$) image. However, in the performance evaluation of all measured items of the proposed scheme, AUC (Area Under ROC (Receiver Operating Characteristic) Curve) by the sensitivity and 1-specificity approached to 1 thus, it is confirmed that the grade of the performance evaluation is rated as 'Excellent (A)'.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.404-411
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• 2009

We introduce in this paper a new method for smooth foldover-free warping of images, based on the vector field deformation technique proposed by Von Funck et al. It allows users to specify the constraints in two different ways: positional constraints to constrain the position of a point in the image and gradient constraints to constrain the orientation and scaling of some parts of the image. From the user-specified constraints, it computes in the image domain a C1-continuous velocity vector field, along which each pixel progressively moves from its original position to the target. The target positions of the pixels are obtained by solving a set of partial derivative equations with the 4th order Runge-Kutta method. We show how our method can be useful for texture mapping with hard constraints. We start with an unconstrained planar embedding of a target mesh using a previously known method (Least Squares Conformal Map). Then, in order to obtain a texture map that satisfies the given constraints, we use the proposed warping method to align the features of the texture image with those on the unconstrained embedding. Compared to previous work, our method generates a smoother texture mapping, offers higher level of control for defining the constraints, and is simpler to implement.

• Proceedings of the Korean Printing Society Conference
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• 2000.04a
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• pp.17-24
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• 2000

The Joint Photographic Experts Group (JPEG) is a standara still-image compression technique, established by the International for Standardization (ISO) and International Telecommunication Standardization Sector (ITUT). The standard is intended to be utilized in the various kinds of color still imaging systems as a standard color image coding format. Because JPEG is a lossy compression, the decompressed image pixel values are nto the same as values before compression. Image of JPEG compression is often made to JPEG recompression at saving to apply JPEG compression of color image. In general, JPEG is a lossy compression and compression image is predicted to be varied image quality according to recompressed Q-factor. Various distortions of JPEG compression and JPEG recompression has been reported in previous paper. In this paper, we compress four difference color samples (photo image, gradient image, vector drawing image, text image) according to various Q-factor, and then compressed images are recompressed according to various Q-factor once again. As the results, we inspect variation of quality and file size of recompressed color image, and ensure the optimum recompression factor.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.117-123
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• 2018

In this study, we suggest a fast image reconstruction scheme using Poisson equation from image gradient domain. In this approach, using the Poisson equation, a guided vector field is created by employing source and target images within a selected region at the first step. Next, the guided vector is used in generating the result image. We analyze the problem of reconstructing a two-dimensional function that approximates a set of desired gradients and a data term. The joined data and gradients are able to work like modifying the image gradients while staying close to the original image. Starting with this formulation, we have a screened Poisson equation known in physics. This equation leads to an efficient solution to the problem in FFT domain. It represents the spatial filters that solve the two-dimensional screened Poisson model and shows gradient scaling to be a well-defined sharpen filter that generalizes Laplace sharpening. We demonstrate the results using a discrete cosine transformation based this Poisson model.