• Journal of the Korea Computer Industry Society
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• v.3 no.7
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• pp.927-936
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• 2002

This paper presents the extraction of a feature by motion vector for efficient content-based retrieval for digital video. in this paper, divided by general size block for the current frame by video, using BMA(block matching algorithm) for an estimate by block move based on a time frame. but in case BMA appeared on a different pattern fact of motion in the vector obtain for the BMA. solve in this a problem to application for full search method this method is detected by of on many calculations. I propose an alternative plan in this paper Limit the search region to $\pm$15 and search is a limit integer pixel. a result, in this paper is make an estimate motion vector in more accurately using motion vector in adjoin in blocks. however, refer to the block vector because occurrence synchronism. Such addition information is get hold burden receive to transmit therefore, forecasted that motion feature each block and consider for problems for establish search region. in this paper Algorithm based to an examination Motion Estimation method by for motion Compensation is proposed.

• Transactions on Semiconductor Engineering
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• v.2 no.1
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• pp.17-20
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• 2024

This paper presents a novel lightweight object detection model tailored for low-powered edge devices, addressing the limitations of traditional resource-intensive computer vision models. Our proposed detector, inspired by the Single Shot Detector (SSD), employs a compact yet robust network design. Crucially, it integrates an 'enhancer block' that significantly boosts its efficiency in detecting smaller objects. The model comprises two primary components: the Light_Block for efficient feature extraction using Depth-wise and Pointwise Convolution layers, and the Enhancer_Block for enhanced detection of tiny objects. Trained from scratch on the Udacity Annotated Dataset with image dimensions of 300x480, our model eschews the need for pre-trained classification weights. Weighing only 5.5MB with approximately 0.43M parameters, our detector achieved a mean average precision (mAP) of 27.7% and processed at 140 FPS, outperforming conventional models in both precision and efficiency. This research underscores the potential of lightweight designs in advancing object detection for edge devices without compromising accuracy.

• Journal of IKEEE
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• v.17 no.3
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• pp.241-247
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• 2013

This paper presents the design of a System on Programmable Chip (SoPC) based on Field Programmable Gate Array (FPGA) for speech recognition in which Mel-Frequency Cepstral Coefficients (MFCC) for speech feature extraction and Vector Quantization for recognition are used. The implementing process of the speech recognition system undergoes the following steps: feature extraction, training codebook, recognition. In the first step of feature extraction, the input voice data will be transformed into spectral components and extracted to get the main features by using MFCC algorithm. In the recognition step, the obtained spectral features from the first step will be processed and compared with the trained components. The Vector Quantization (VQ) is applied in this step. In our experiment, Altera's DE2 board with Cyclone II FPGA is used to implement the recognition system which can recognize 64 words. The execution speed of the blocks in the speech recognition system is surveyed by calculating the number of clock cycles while executing each block. The recognition accuracies are also measured in different parameters of the system. These results in execution speed and recognition accuracy could help the designer to choose the best configurations in speech recognition on SoPC.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.1
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• pp.11-18
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• 2001

In this paper, we proposed the image compression algorithm using triangular feature based GHA. In feature extraction, the input images are divided into eight areas of triangular shape, that has positional information for face image compression. The proposed algorithm reduces blocking effects in image reconstruction and contains informations of face feature and shapes of face as input images are divided into eight. We used triangular feature extraction for positional information and GHA for shape information of face images. Simulation results show that the proposed algorithm has a better performance than the block based K-means and non-parsed image based GHA in PSNR at the same bpp.

• Journal of information and communication convergence engineering
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• v.13 no.4
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• pp.275-279
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• 2015

There are several methods to record three dimensional (3D) information of objects such as lens array based integral imaging, synthetic aperture integral imaging (SAII), computer synthesized integral imaging (CSII), axially distributed image sensing (ADS), and axially distributed stereo image sensing (ADSS). ADSS method is capable of recording partially occluded 3D objects and reconstructing high-resolution slice plane images. In this paper, we present a computational method for depth extraction of partially occluded 3D objects using ADSS. In the proposed method, the high resolution elemental stereo image pairs are recorded by simply moving the stereo camera along the optical axis and the recorded elemental image pairs are used to reconstruct 3D slice images using the computational reconstruction algorithm. To extract depth information of partially occluded 3D object, we utilize the edge enhancement and simple block matching algorithm between two reconstructed slice image pair. To demonstrate the proposed method, we carry out the preliminary experiments and the results are presented.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.8-14
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• 2009

A Hidden Markov Model(HMM)-based information extraction method is proposed in this paper. The proposed extraction method is applied to extraction of products' prices. The input of the proposed IESHMM is the URLs of a search engine's interface, which contains the names of the product types. The output of the system is the list of extracted slots of each product: name, price, image, and URL. With the observation data set Maximum Likelihood algorithm and Baum-Welch algorithm are used for the training of HMM and The Viterbi algorithm is then applied to find the state sequence of the maximal probability that matches the observation block sequence. When applied to practical problems, the proposed HMM-based system shows improved results over a conventional method, PEWEB, in terms of recall ration and accuracy.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.333-336
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• 2001

본 논문에서는 영상 시퀀스 상에서 물체의 가려짐을 고려하여 상대적인 깊이 순서에 의해 정렬되는 계층을 분리하기 위한 새로운 움직임 분할 방법을 제안한다. 블록을 기반으로 한 움직임 추정 및 클러스터링 과정을 통하여 각 계층에 대한 블록영역을 구하고, 이 블록영역에 대하여 윤곽선 추출을 이용하여 각 계층에 대한 정확한 객체를 분리할 수 있다. 이러한 움직임 분할방법을 통한 동영상의 계층적인 표현은 영상에서 원하지 않는 물체, 전경, 배경의 제거나 기존의 영상을 이용한 새로운 영상의 합성에 이용될 수 있으며, 분할을 통해 얻어진 객체는 영상 압축, 영상 합성 등을 위한 데이터베이스에 저장되어 응용될 수 있다.

• The Journal of the Korean dental association
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• v.57 no.12
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• pp.768-777
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• 2019

Alveolar bone resorption are unpredictable and always occur after tooth extraction. Such bone resorption causes insufficient alveolar ridge which make implant placement difficult. There are many techniques to increase the alveolar ridge. Representative procedures include ridge split, guided bone regeneration, bone graft using autogenous block bone, and alveolar distraction. In each procedure, there are indications and complications. Depending on the shape and the width of bone defects, we can choose procedures for horizontal bone augmentation and vertical bone augmentation.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.424-426
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• 2001

신문, 잡지, 공문서, 영수증 등의 문서로부터 필요한 정보를 자동화하여 처리할 수 있는 문서영상 이해 시스템의 구현에 있어서 문서영상에 존재하는 문자를 추출하는 연구는 문자 인식의 전처리 단계로서 매우 중요한 의미를 지니고 있다. 하지만 현 시점에서 문서 자체가 가지는 다양한 형태 및 배경 등에 의하여 범용화되고 일반화된 방법을 찾기란 매우 어려운 실정이다. 본 논문에서는 특히 배경이 선이나 도표 등으로 이루어진 문서 영상에서 Hough Transform을 사용하여 기울어짐을 보정하고 문자들이 선에 겹친 부분을 효과적으로 보정하며 추출된 영역에 대한 분할 및 합병 과정을 거쳐 최종적으로 완전한 문자 영역을 추출하는 방법에 대하여 다룬다.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.133-136
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• 2002

In this paper, we propose a method to extract vertical stripes projected on human face using Gabor filter, Previous work cannot extract continuous vertical stripes in the eye and mouth region due to their horizontal lines, Proposed method use Gator filter adaptively according to main frequencies and directions of stripes in each block. Experimental results show that Proposed method can extract continuous vertical stripes in the eye and mouth region