• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2007년도 하계종합학술대회 논문집
• /
• pp.251-252
• /
• 2007

The thesis proposed the Text Extraction Algorithm which is a text extraction algorithm which uses the Coiflet Wavelet, YCbCr Color model and the close curve edge feature of adaptive LoG Operator in order to complement the demerit of the existing research which is weak in complexity of background, variety of light and disordered line and similarity of text and background color. This thesis is simulated with natural images which include naturally text area regardless of size, resolution and slant and so on of image. And the proposed algorithm is confirmed to an excellent by compared with an existing extraction algorithm in same image.

• Journal of Microbiology and Biotechnology
• /
• 제10권5호
• /
• pp.724-727
• /
• 2000

A Phenanthrene-degrading bacterium, Strain 1-21 was isolated from oil-contaminated soil. This strain was a Gram-negative, aerobic, and rod-shaped bacterium, and exhibited a 99% sequence similarity of 16S rDNA to that of Sphingomonas subarctica. The major cellular fatty acid was a summed feature 7(18:1 w7c, 18:1 w9t, 18:1 s12t), which is a characteristic of the Sphingomonas species. When 200 and 1,000 ppm of phenanthrene was added as the sole carbon source, Strain 1-21 degraded 98% and 67% after 10 days of incubation, respectively. Futhermore, this strain was also able to utilized naphthalene and fluorene as sole carbon and energy sources.

• 한국군사과학기술학회지
• /
• 제13권3호
• /
• pp.445-452
• /
• 2010

Adequate segmentation of target objects from the background plays an important role for the performance of automatic target recognition(ATR) system. This paper presents a new segmentation algorithm using fuzzy thresholding to extract a target. The proposed algorithm consists of two steps. In the first step, the region of interest(ROI) including the target can be automatically selected by the proposed robust method based on the frame difference of each image sensor. In the second step, fuzzy thresholding with a proposed membership function is performed within the only ROI selected in the first step. The proposed membership function is based on the similarity of intensity and the adjacency of target area on each image. Experimental results applied to real CCD/IR images show a good performance and the proposed algorithm is expected to enhance the performance of ATR system using multi-sensors.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
• /
• pp.392-395
• /
• 2003

This paper describes a new iris segmentation and recognition method, which is robust to noises. Combining statistical classification and elastic boundary fitting, the iris is first segmented. Then, the localized iris image is smoothed by a convolution with a Gaussian function, down-sampled by a factor of filtered with a Laplacian operator, and quantized using the Lloyd-Max method. Since the quantized output is sensitive to a small shift of the full-resolution iris image, the outputs of the Laplacian operator are computed for all space shifts. The quantized output with maximum entropy is selected as the final feature representation. An appropriate formulation of similarity measure is defined for the classification of the quantized output. Experimentally we showed that the proposed method produces superb performance in iris segmentation and recognition.

• Journal of Information Processing Systems
• /
• 제17권1호
• /
• pp.203-212
• /
• 2021

To eliminate ambiguities in the existing methods to simplify Chinese pronunciation learning, we propose a model that can predict the pronunciation of Chinese characters automatically. The proposed model relies on a statistical machine translation (SMT) framework. In particular, we consider the components of Chinese characters as the basic unit and consider the pronunciation prediction as a machine translation procedure (the component sequence as a source sentence, the pronunciation, pinyin, as a target sentence). In addition to traditional features such as the bidirectional word translation and the n-gram language model, we also implement a component similarity feature to overcome some typos during practical use. We incorporate these features into a log-linear model. The experimental results show that our approach significantly outperforms other baseline models.

• International Journal of Internet, Broadcasting and Communication
• /
• 제13권2호
• /
• pp.156-165
• /
• 2021

In this paper, we propose an histogram weighted centroid based Siamese region proposal network for object tracking. The original Siamese region proposal network uses two identical artificial neural networks which take two different images as the inputs and decide whether the same object exist in both input images based on a similarity measure. However, as the Siamese network is pre-trained offline, it experiences many difficulties in the adaptation to various online environments. Therefore, in this paper we propose to incorporate the histogram weighted centroid feature into the Siamese network method to enhance the accuracy of the object tracking. The proposed method uses both the histogram information and the weighted centroid location of the top 10 color regions to decide which of the proposed region should become the next predicted object region.

• 한국멀티미디어학회논문지
• /
• 제25권5호
• /
• pp.676-684
• /
• 2022

As realistic media are widespread in various image processing areas, image or video compression is one of the key technologies to enable real-time applications with limited network bandwidth. Generally, image or video compression cause the unnecessary compression artifacts, such as blocking artifacts and ringing effects. In this study, we propose a Deep Residual Channel-attention Network, so called DRCAN, which consists of an input layer, a feature extractor and an output layer. Experimental results showed that the proposed DRCAN can reduced the total memory size and the inference time by as low as 47% and 59%, respectively. In addition, DRCAN can achieve a better peak signal-to-noise ratio and structural similarity index measure for compressed images compared to the previous methods.

• Journal of Information Processing Systems
• /
• 제19권1호
• /
• pp.80-88
• /
• 2023

RGB-thermal (RGB-T) tracking using unmanned aerial vehicles (UAVs) involves challenges with regards to the similarity of objects, occlusion, fast motion, and motion blur, among other issues. In this study, we propose dynamic tracking aggregation (DTA) as a unified framework to perform object detection and data association. The proposed approach obtains fused features based a transformer model and an L1-norm strategy. To link the current frame with recent information, a dynamically updated embedding called dynamic tracking identification (DTID) is used to model the iterative tracking process. For object association, we designed a long short-term tracking aggregation module for dynamic feature propagation to match spatial and temporal embeddings. DTA achieved a highly competitive performance in an experimental evaluation on public benchmark datasets.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2010년도 추계학술발표대회
• /
• pp.197-200
• /
• 2010

단백질의 서열 정보와 기능 정보의 양이 증가함에 따라 컴퓨터 실험을 통한 단백질의 기능 예측이 가능해졌으며 정확성이 높은 예측 시스템을 개발하려는 여러 연구가 시도되고 있다. 대표적인 방법으로 서열 유사도를 기반으로 기능 예측을 하는 시스템이 제안되었으나 단백질 중에는 서열이 유사하지만 기능이 다르거나 또는 서열은 다름에도 불구하고 기능이 같은 단백질이 존재하기 때문에 서열의 유사도 만을 이용해서는 단백질의 기능 예측을 어렵다. 이러한 유사도 방법의 단점을 극복하기 위해 단백질 서열로부터 추출한 특징을 기반으로 분류하는 방법도 제안되었다. 본 논문에서는 이러한 기존 방법들의 장점을 얻기 위하여 서열 유사도 방법과 특징 기반 방법을 융합한 단백질 기능 예측 시스템을 제안하고 예측 정확성 분석을 위한 실험을 실시하였다. 실험의 결과에 따르면 제안된 융합시스템이 서열 유사도만을 이용한 방법과 특징 기반 방법보다 좋은 예측 정확률을 갖는 것으로 분석되었다.

• International Journal of Computer Science & Network Security
• /
• 제23권3호
• /
• pp.187-192
• /
• 2023

With development of information technology and necessity for high security, using different identification methods has become very important. Each biometric feature has its own advantages and disadvantages and choosing each of them depends on our usage. Retinal scanning is a bio scale method for identification. The retina is composed of vessels and optical disk. The vessels distribution pattern is one the remarkable retinal identification methods. In this paper, a new approach is presented for identification via retinal images using LBP and hog methods. In the proposed method, it will be tried to separate the retinal vessels accurately via machine vision techniques which will have good sustainability in rotation and size change. HOG-based or LBP-based methods or their combination can be used for separation and also HSV color space can be used too. Having extracted the features, the similarity criteria can be used for identification. The implementation of proposed method and its comparison with one of the newly-presented methods in this area shows better performance of the proposed method.