• Title/Summary/Keyword: Compression classes

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Adaptive Classification of Subimages by the Fuzzy System for Image Data Compression (퍼지시스템에 의한 부영상의 적응분류와 영상데이타 압축에의 적용)

  • Kong, Seong-Gon
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.43 no.7
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    • pp.1193-1205
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    • 1994
  • This paper presents a fuzzy system that adaptively classifies subimages to four classes according to image activity distribution. In adaptive transform image coding, subimage classification improves the compression performance by assigning different bit maps to different classes. A conventional classification method sorts subimages by their AC energy and divides them to classes with equal number of subimages. The fuzzy system provides more flexible classification to natural images with various distribution of image details than does the conventional method. Clustering of training data in the input-output product space generated the fuzzy rules for subimage classification. The fuzzy system of small number of fuzzy rules successfully classified subimages to improve the compression performance of the transform image coding without sorting of AC energies.

A Comparison of Imported Medical Compression Stockings by Manufacturing Country (수입 의료용 압박스타킹의 제조국가별 비교)

  • Do, Wol-Hee;Kim, Nam-Soon
    • Journal of the Korean Society of Clothing and Textiles
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    • v.36 no.3
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    • pp.335-345
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    • 2012
  • This study provides product survey data for the development of medical compression stockings. An investigation analyzed imported medical compression stockings of 40 brands from 6 countries sold in the Korean market, such as Jobst$^{(R)}$, Therafirm$^{(R)}$, Rxtar$^{(R)}$, Varicoin$^{(R)}$, and Sheer&Soft (USA), Sigvaris Venosan$^{(R)}$ 4000 (Switzerland), Best$^{(R)}$ and Segreta$^{(R)}$ (Italy), Venex$^{(R)}$, Star cotton, Doktus$^{(R)}$, Maxis$^{(R)}$, Maxis$^{(R)}$ Cotton, Lastofa$^{(R)}$, and Memory Aloe Vera (Germany), and Gunze (Japan), Venos and Yolanda (Taiwan). The main fibers of compression stockings were nylon and spandex; in addition, the fiber content was different by country and brand. The number of compression classes of imported products was USA (5), Italy (5), Germany (4), Switzerland (3), Japan (3), and Taiwan (3). For basic body measurements, USA and Swiss brands used ankle circumference, calf circumference, thigh circumference, calf length, and thigh length. Italian brands used height and weight, and Japanese brands used height and hip circumference. German brands used subdivided circumferences such as ankle circumference, calf circumference, knee circumference, middle thigh circumference, and thigh circumference.

A Experimental Study on the Comparison of the Compression Strength Characteristics of Mortar using the Blast-Furnace Slag Sand (슬래그모래를 사용한 모르터의 압축강도특성 비교에 관한 실험적 연구)

  • 김종락;김성식;이복만;임남기;정상진
    • Proceedings of the Korea Concrete Institute Conference
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    • 1999.04a
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    • pp.40-45
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    • 1999
  • This experimental study presents the strength properties of mortar using the blast-furnace slag sand. The mix disign of this study is based on the each three classes of unit water; (250, 275, 300)kg/㎥ and four classes of W/C; (45, 50, 55, 60)% and substitution rate(0, 25, 50, 75, 100)%. It gives following result. As W/C ratio increase, the strength is decrease. In case of mortar using air-cooled blast-furnace slag sand, the 3-days and 7-days compression strength is increase as substitution rate is higher. But in case of the mortar using the quenched blast-furnace slag sand, the compression strength is decrease as substitution rate is higher.

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Vector Quantization Compression of the Still Image by Multilayer Perceptron (다층 신경회로망 학습에 의한 정지 영상의 벡터)

  • Lee, Sang-Chan;Choe, Tae-Wan;Kim, Ji-Hong
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.2
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    • pp.390-398
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    • 1996
  • In this paper, a new image compression algorithm using the generality of the multilaryer perceptron is proposed. Proposed algorithm classifies image into some classes, and trains them through the multilayer perceptron. Multilayer perceptron which trained by the above method can do compression and reconstruction of the nontrained image by the generality. Also, it reduces memory size of the side of receiver and quantization error. For the experiment, we divide Lena image into 16 classes and train them through one multilayer perceptron. The experimental results show that we can get excellent reconstruction images by doing compression and reconstruction for Lena image, Dollar image and Statue image.

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Comparison of Medical Compression Garments by Manufacturing Country (의료용 화상환자 압박복의 제조 국가별 비교)

  • Cho, Shin-Hyun
    • Journal of the Korea Fashion and Costume Design Association
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    • v.17 no.4
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    • pp.31-39
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    • 2015
  • A special medical compression garment has been developed to be worn after surgery or treatment using an elastic fiber in which the amount of compression can be adjusted to a specified targeted area to reduce the formation of hypertrophic scarring. In order to develop this medical compression garments, specialized technical skill in fiber, compression class and body measurements are needed. This study provides product survey data for the development of medical compression garments. An investigation analyzed medical compression garments of 16 brands from 6 countries sold in the Korean market & online, such as Make Me Heal, Jobst, Bio Concepts, Design Veronique$^{(R)}$ Nouvelle and Leonisa$^{(R)}$ (USA), Respire(Germany), Malcom$^{(R)}$, Holistic garments and Jobskin(UK), Technomed, kanav Healthcare and Sindhoori surgicals(India), Soo medical and C&C medical(Korea), Secondskin(Australia). The main fibers of compression garments were nylon and spandex: in addition, the fiber content was different by country and brand. The number of compression classes of products was USA(4), UK(4), and India(4). For body measurements, USA and many brands used (bust, under bust, waist, hip, thigh, knee, calf, ankle, upper arm, elbow, wrist, armhole bicep) circumference and length.

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Multispectral Image Compression Using Classification in Wavelet Domain and Classified Inter-channel Prediction and Selective Vector Quantization in Wavelet Domain (웨이브릿 영역에서의 영역분류와 대역간 예측 및 선택적 벡터 양자화를 이용한 다분광 화상데이타의 압축)

  • 석정엽;반성원;김병주;박경남;김영춘;이건일
    • Proceedings of the IEEK Conference
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    • 2000.06d
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    • pp.31-34
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    • 2000
  • In this paper, we proposed multispectral image compression method using CIP (classified inter-channel prediction) and SVQ (selective vector quantization) in wavelet domain. First, multispectral image is wavelet transformed and classified into one of three classes considering reflection characteristics of the subband with the lowest resolution. Then, for a reference channel which has the highest correlation with other channels, the variable VQ is performed in the classified intra-channel to remove spatial redundancy. For other channels, the CIP is performed to remove spectral redundancy. Finally, the prediction error is reduced by performing SVQ. Experiments are carried out on a multispectral image. The results show that the proposed method reduce the bit rate at higher reconstructed image quality and improve the compression efficiency compared to conventional method.

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On-Board Satellite MSS Image Compression

  • Ghassemian, Hassan;Amidian, Asghar
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.645-647
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    • 2003
  • In this work a new method for on-line scene segmentation is developed. In remote sensing a scene is represented by the pixel-oriented features. It is possible to reduce data redundancy by an unsupervised segment-feature extraction process, where the segment-features, rather than the pixelfeatures, are used for multispectral scene representation. The algorithm partitions the observation space into exhaustive set of disjoint segments. Then, pixels belonging to each segment are characterized by segment features. Illustrative examples are presented, and the performance of features is investigated. Results show an average compression more than 25, the classification performance is improved for all classes, and the CPU time required for classification is reduced by the same factor.

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KOHONEN NETWORK FOR ADAPTIVE IMAGE COMPRESSION (영상압축을 위한 코넨네트워크)

  • 손형경;이영식;배철수
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2001.10a
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    • pp.571-574
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    • 2001
  • In our paper, We propose an efficient adaptive coding method using kohonen neural network. An efficient adaptive encoding method using Kohonen net work is discribed through the analysis of those compression methods with the application of the neural network. In order to increase the compression ratio, a image is first divided into 8*8 subimages, then all subimages are transformed by DCT. These DCT sub-blocks are divided into N(4) classes by Kohonen network. Hits are distributed according to the variance of the DCT sub-block. Thus we get N(4)bit allocation matrices. Excellent performance is shown by the computer simulation. so we found that our proposed method is better then classifing subimages by AC energy.

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Material Properties and Compressibility Using Heckel and Kawakita Equation with Commonly Used Pharmaceutical Excipients

  • Choi, Du-Hyung;Kim, Nam-Ah;Chu, Kyung-Rok;Jung, Youn-Jung;Yoon, Jeong-Hyun;Jeong, Seong-Hoon
    • Journal of Pharmaceutical Investigation
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    • v.40 no.4
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    • pp.237-244
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    • 2010
  • This study investigated basic material properties and compressibility of commonly used pharmaceutical excipients. Five classes of excipients are selected including starch, lactose, calcium phosphate, microcrystalline cellulose (MCC), and povidone. The compressibility was evaluated using compression parameters derived from Heckel and Kawakita equation. The Heckel plot for lactose and dicalcium phosphate showed almost linear relationship. However, for MCC and povidone, curves in the initial phase of compression were observed followed by linear regions. The initial curve was considered as particle rearrangement and fragmentation and then plastic deformation at the later stages of the compression cycle. The Kawakita equation showed MCC exhibited higher compressibility, followed by povidone, lactose, and calcium phosphate. MCC undergoes significant plastic deformation during compression bringing an extremely large surface area into close contact and facilitating hydrogen bond formation between the plastically deformed, adjacent cellulose particles. Lactose compacts are consolidated by both plastic deformation and fragmentation, but to a larger extent by fragmentation. Calcium phosphate has poor binding properties because of its brittle nature. When formulating tablets, selection of suitable pharmaceutical excipients is very important and they need to have good compression properties with decent powder flowability. Material properties tested in this study might give a good guide how to select excipients for tablet formulations and help the formulation scientists design the optimum ones.

Adaptive Transform Image Coding by Fuzzy Subimage Classification

  • Kong, Seong-Gon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.2 no.2
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    • pp.42-60
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    • 1992
  • An adaptive fuzzy system can efficiently classify subimages into four categories according to image activity level for image data compression. The system estimates fuzzy rules by clustering input-output data generated from a given adaptive transform image coding process. The system encodes different images without modification and reduces side information when encoding multiple images. In the second part, a fuzzy system estimates optimal bit maps for the four subimage classes in noisy channels assuming a Gauss-Markov image model. The fuzzy systems respectively estimate the sampled subimage classification and the bit-allocation processes without a mathematical model of how outputs depend on inputs and without rules articulated by experts.

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