• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.65-70
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• 2013

Recently, the field of computer vision has been actively researched through digital image which can be easily generated as the development and expansion of digital camera technology. Especially, research that extracts and utilizes the feature in image has been actively carried out. The image stitching is a method that creates the high resolution image using features extract and match. Image stitching can be widely used in military and medical purposes as well as in variety fields of real life. In this paper, we have proposed efficient image stitching method using fast feature descriptor extraction and matching based on SURF algorithm. It can be accurately, and quickly found matching point by reduction of dimension of feature descriptor. The feature descriptor is generated by classifying of unnecessary minutiae in extracted features. To reduce the computational time and efficient match feature, we have reduced dimension of the descriptor and expanded orientation window. In our results, the processing time of feature matching and image stitching are faster than previous algorithms, and also that method can make natural-looking stitched image.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1083-1094
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• 2020

Recognizing plant species based on leaf images is challenging because of the large inter-class variation and inter-class similarities among different plant species. The effective extraction of leaf descriptors constitutes the most important problem in plant leaf recognition. In this paper, a multi-scale angular description method is proposed for fast and accurate leaf recognition and retrieval tasks. The proposed method uses a novel scale-generation rule to develop an angular description of leaf contours. It is parameter-free and can capture leaf features from coarse to fine at multiple scales. A fast Fourier transform is used to make the descriptor compact and is effective in matching samples. Both support vector machine and k-nearest neighbors are used to classify leaves. Leaf recognition and retrieval experiments were conducted on three challenging datasets, namely Swedish leaf, Flavia leaf, and ImageCLEF2012 leaf. The results are evaluated with the widely used standard metrics and compared with several state-of-the-art methods. The results and comparisons show that the proposed method not only requires a low computational time, but also achieves good recognition and retrieval accuracies on challenging datasets.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.125-128
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• 2000

The conventional fractal decoding was required a vast amount computational complexity. Since every range blocks was implemented to IFS(iterated function system). In order to improve this, it has been suggested to that each range block was classified to iterated and non-iterated regions. If IFS region is contractive, then it can be performed a fast decoding. In this paper, a searched region of the domain in the encoding is limited to the range region that is similar with the domain block, and IFS region is a minimum. So, it can be performed a fast decoding by reducing the computational complexity for IFS in fractal image decoding.

• Journal of Biomedical Engineering Research
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• v.26 no.1
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• pp.23-30
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• 2005

3D virtual endoscopy has been used as an alternative non-invasive procedure for visualization of hollow organs. However, due to computational complexity, this is a time-consuming procedure. In this paper, we propose a fast volume rendering algorithm based on perspective ray casting for virtual endoscopy. As a pre-processing step, the algorithm divides a volume into hierarchical blocks and classifies them into opaque or transparent blocks. Then, in the first step, we perform ray casting only for sub-sampled pixels on the image plane, and determine their pixel values and depth information. In the next step, by reducing the sub-sampling factor by half, we repeat ray casting for newly added pixels, and their pixel values and depth information are determined. Here, the previously obtained depth information is utilized to reduce the processing time. This step is recursively performed until a full-size rendering image is acquired. Experiments conducted on a PC show that the proposed algorithm can reduce the rendering time by 70- 80% for bronchus and colon endoscopy, compared with the brute-force ray casting scheme. Using the proposed algorithm, interactive volume rendering becomes more realizable in a PC environment without any specific hardware.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.67-75
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• 1999

In this paper, we present an ASIC(Application Specific Integrated Circuit) design of wavelet transform filter Wavelet transform is used in lots of application fields which include image compression, because it has an excellent energy compaction. The operation characteristic and performance of wavelet transform filter are analyzed by using verilog-HDL(Hardware Description Language). In this paper, the designed wavelet transform filter uses line memory to improve data processing rate. Generally, when it reads and writes data of DRAM by using Fast Page Mode, input and output processing is very fast in horizontal direction but substantially slow in vertical direction. The use of line memory solves this low speed processing problem. As a result, though the size of the chip is getting larger, processing time for an image frame becomes 4.66ms. Generally, since the limit of 1 frame processing time on the data of TV video is 33ms, so it is appropriate for TV video.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.1
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• pp.25-29
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• 2013

Recently ARM processor's processing power has been increasing rapidly as it has been applied to consumer electronics products. Because of its computing power and low power consumption, it is used to various embedded systems.( including vision processing systems.) Embedded linux that provides well-made platform and GUI is also a powerful tool for ARM based embedded systems. So short period to develop is one of major advantages to the ARM based embedded system. However, for real-time date processing applications such as an image processing system, ARM needs additional equipments such as FPGA that is suitable to parallel processing applications. In this paper, we developed an embedded system using ARM processor and FPGA. FPGA takes time consuming image preprocessing and numerical algorithms needs floating point arithmetic and user interface are implemented using the ARM processor. Overall processing speed of the system is 60 frames/sec of VGA images.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.221-224
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• 2005

대부분의 영상은 다양한 이유(노이즈, 전송과정 중 발생하는 문제 등)로 인해 항상 좋은 품질을 보여주진 못한다. 이렇게 훼손된 영상의 복원은 다양한 정보를 제공한다. 이런 훼손된 영상을 복원하기 위해 Median filtering과 같은 기존의 처리 방법들은 주변 화소(Pixel)를 평활화(Smoothing) 처리를 하기 때문에 noise 처리에는 좋으나 원 영상의 중요한 에지 성분까지도 평활화 처리를 함으로써 에지 부분의 공간적 이동을 초래할 수 있다. 이러한 문제점을 해결하기 위하여 image inpainting 방법이 제안되고 있으며, inpainting 기법에는 편미분 방정식(PDE)을 이용한 방법, 텍스쳐 병합 기반의 방법들이 있다. 그러나 이러한 inpainting 기법들은 연산 수행시간이 많이 소요되는 단점이 있다. 따라서 본 연구에서는 image inpainting을 수행시 소요되는 연산시간을 줄이는 fast image inpainting 알고리즘을 제안한다.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.475-480
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• 1994

For the effective management of medical images, it becomes popular to use computing machines in medical practice, namely PACS. However, the amount of image data is so large that there is a lack of storage space. We usually use data compression techniques to save storage, but the process speed of machines is not fast enough to meet surgical requirement. So a special hardware system processing medical images faster is more important than ever. To meet the demand for high speed image processing, especially image compression and decompression, we designed and implemented the medical image CODEC (COder/DECoder) based on MISD (Multiple Instruction Single Data stream) architecture to adopt parallelism in it. Considering not being a standard scheme of medical image compression/decompression, the CODEC is designed programable and general. In this paper, we use JPEG (Joint Photographic Experts Group) algorithm to process images and evalutate the CODEC.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1108-1118
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• 2019

Non-local means (NLM) algorithm is an effective and successful denoising method, but it is computationally heavy. To deal with this obstacle, we propose a novel NLM algorithm with fuzzy metric (FM-NLM) for image denoising in this paper. A new feature metric of visual features with fuzzy metric is utilized to measure the similarity between image pixels in the presence of Gaussian noise. Similarity measures of luminance and structure information are calculated using a fuzzy metric. A smooth kernel is constructed with the proposed fuzzy metric instead of the Gaussian weighted L2 norm kernel. The fuzzy metric and smooth kernel computationally simplify the NLM algorithm and avoid the filter parameters. Meanwhile, the proposed FM-NLM using visual structure preferably preserves the original undistorted image structures. The performance of the improved method is visually and quantitatively comparable with or better than that of the current state-of-the-art NLM-based denoising algorithms.

• ETRI Journal
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• v.38 no.4
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• pp.599-605
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• 2016

For the implementation of a real-time holographic camera, fast and automatic holographic image reconstruction is an essential technology. In this paper, we propose a new automatic depth-detection algorithm for fast holography reconstruction, which is particularly useful for optical scanning holography. The proposed algorithm is based on the inherent phase difference information in the heterodyne signals, and operates without any additional optical or electrical components. An optical scanning holography setup was created using a heterodyne frequency of 4 MHz with a 500-mm distance and 5-mm depth resolution. The reconstruction processing time was measured to be 0.76 s, showing a 62% time reduction compared to a recent study.