• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.213-231
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• 2014

Existing image search systems allow users to search images by keywords, or by example images through content-based image retrieval (CBIR). On the other hand, users might learn more relevant textual information about an image from its text captions or surrounding contexts within documents or Web pages. Without such contexts, it's difficult to extract semantic description directly from the image content. In this paper, we propose an annotation watermarking system for users to embed text descriptions, and retrieve more relevant textual information from similar images. First, tags associated with an image are converted by two-dimensional code and embedded into the image by discrete wavelet transform (DWT). Next, for images without annotations, similar images can be obtained by CBIR techniques and embedded annotations can be extracted. Specifically, we use global features such as color ratios and dominant sub-image colors for preliminary filtering. Then, local features such as Scale-Invariant Feature Transform (SIFT) descriptors are extracted for similarity matching. This design can achieve good effectiveness with reasonable processing time in practical systems. Our experimental results showed good accuracy in retrieving similar images and extracting relevant tags from similar images.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.643-649
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• 2016

This paper presents a new image cache algorithm for real-time implementation of high-resolution color image warping. The cache memory is divided into four cache memory modules for simultaneous readout of four input image pixels in consideration of the color filter array (CFA) pattern of an image sensor and CFA image warping. In addition, a pipeline structure from the cache memory to an interpolator is shown to guarantee the generation of an output image pixel at each system clock cycle. The proposed image cache algorithm is applied to an FPGA-based real-time color image warping, and experimental results are presented to show the validity of the proposed method.

• Journal of the Semiconductor & Display Technology
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• v.15 no.3
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• pp.51-56
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• 2016

This paper proposes a new image enhancement method for an infrared thermal image. The proposed method uses both Laplacian and Prewitt edge detectors. Without a visible light, it uses an infrared image for the edge detection. The method subtracts contour images from the infrared thermal image. It results black contours of objects in the infrared thermal image. That makes the objects in the infrared thermal image distinguished clearly. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using various infrared thermal images. The results show that the proposed method is successful for image enhancement of an infrared thermal image.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.275-288
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• 2023

Many image edge details are easily lost in the image denoising process, and the smooth image regions are prone to produce jagged. In this paper, we propose a wavelet-based image global k- singular value decomposition variational method to remove image noise. A layer of wavelet decomposition is applied to the noisy image first. Then, the image global k-singular value decomposition (IGK-SVD) method is used to remove the random noise of low-frequency components. Furthermore, a constructed variational denoising method (VDM) removes the random noise in the high-frequency component. Finally, the denoised image is obtained by wavelet reconstruction. The experimental results show that the proposed method's peak signal-to-noise ratio (PSNR) value is higher than other methods, and its structural similarity (SSIM) value is closer to one, indicating that the proposed method can effectively suppress image noise while retaining more image edge details. The denoised image has better denoising effects.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.979-982
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• 2002

Compressing image data by using Vector Quantization (VQ)［1］-［3］will compare Training Vectors with Codebook. The result is an index of position with minimum distortion. The implementing Random Codebook will reduce the image quality. This research presents the Splitting solution ［4］,［5］to implement the Codebook, which improves the image quality［6］by the average Training Vectors, then splits the average result to Codebook that has minimum distortion. The result from this presentation will give the better quality of the image than using Random Codebook.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.607-612
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• 2008

This paper proposes a robot visual servo approach based on image appearance and a wavelet function neural network. The inputs of the wavelet neural network are changes of image features or the elements of image appearance vector, and the outputs are changes of robot joint angles. Image appearance vector is calculated by using eigen subspace transform algorithm. The proposed approach does not need a priori knowledge of the robot kinematics, hand-eye geometry and camera models. The experiment results on a real robot system show that the proposed method is practical and simple.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.260-262
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• 2003

New Image registration techniques are developed for determining geometric distortions between two images of the same scene. First, the properties of the Fourier transform of a two dimensional function under the affine transformation are given. As a result, techniques for the estimation of the coefficients of the distortion model using the spectral frequency information are developed. Image registration can be achieved by applying the fast Fourier transform (FFT) technique for cross correlation of misregistered imagery to determine spatial distances. The correlation results may be rather broad, making detection of the peak difficult, what can be suppressed by enhancing cross-correlation technique. Yield greatly improves the delectability and high precision of image misregistration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5268-5285
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• 2016

Digital watermarking techniques are widely applied to protect the integrity and copyright of digital content. In a majority of the literature for watermarking techniques, the watermarked image often causes some distortions after embedding a watermark. For image-quality-concerned users, the distortions from a watermarked image are unacceptable. In this article, we propose a removable watermarking scheme that can restore an original-like image and resist signal-processing attacks to protect the ownership of an image by utilizing the property of singular value decomposition (SVD). The experimental results reveal that the proposed scheme meets the requirements of watermarking robustness, and also reestablishes an image like the original with average PSNR values of 59.07 dB for reconstructed images.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.204-206
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• 2003

In order to utilize remote sensed images effectively, a lot of image classification methods are suggested for many years. But, the accuracy of traditional methods based on pixel-based classification is not high in general. In this study, object oriented classification based on image segmentation is used to classify Landsat images. A necessary prerequisite for object oriented image classification is successful image segmentation. Object oriented image classification, which is based on fuzzy logic, allows the integration of a broad spectrum of different object features, such as spectral values , shape and texture. Landsat images are divided into urban, agriculture, forest, grassland, wetland, barren and water in sochon-gun, Chungcheongnam-do using object oriented classification algorithms in this paper. Preliminary results will help to perform an automatic image classification in the future.

• Journal of Institute of Convergence Technology
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• v.3 no.2
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• pp.45-49
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• 2013

Instant custom embroidered souvenir manufacturing system was studied. Recently customers want to get individually specialized souvenir. We present a modular manufacturing system and implementation of image processing, conversion of punching data. The manufacturing system consist of main module, photographing module and U/I module. We can change the system easily through modularization. Image Processing was necessary for making punching data. We developed sketch typed image processing and image processing which used brightness. Brightness type is suitable for instant embroidered souvenir. This study showed that fusion of embroidery technology and image processing technology can make a new business successfully.