• 제목/요약/키워드: HSI model

검색결과 138건 처리시간 0.028초

Movement Detection Algorithm Using Virtual Skeleton Model (가상 모델을 이용한 움직임 추출 알고리즘)

  • Joo, Young-Hoon;Kim, Se-Jin
    • Journal of the Korean Institute of Intelligent Systems
    • /
    • 제18권6호
    • /
    • pp.731-736
    • /
    • 2008
  • In this paper, we propose the movement detection algorithm by using virtual skeleton model. To do this, first, we eliminate error values by using conventioanl method based on RGB color model and eliminate unnecessary values by using the HSI color model. Second, we construct the virtual skeleton model with skeleton information of 10 peoples. After matching this virtual model to original image, we extract the real head silhouette by using the proposed circle searching method. Third, we extract the object by using the mean-shift algorithm and this head information. Finally, we validate the applicability of the proposed method through the various experiments in a complex environments.

Wear Debris Analysis using the Color Pattern Recognition (칼라 패턴인식을 이용한 마모입자 분석)

  • ;A.Y.Grigoriev
    • Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
    • /
    • 한국윤활학회 2000년도 제31회 춘계학술대회
    • /
    • pp.54-61
    • /
    • 2000
  • A method and results of classification of 4 types metallic wear debris were presented by using their color features. The color image of wear debris was used (or the initial data, and the color properties of the debris were specified by HSI color model. Particle was characterized by a set of statistical features derived from the distribution of HSI color model components. The initial feature set was optimized by a principal component analysis, and multidimensional scaling procedure was used for the definition of classification plane. It was found that five features, which include mean values of H and S, median S, skewness of distribution of S and I, allow to distinguish copper based alloys, red and dark iron oxides and steel particles. In this work, a method of probabilistic decision-making of class label assignment was proposed, which was based on the analysis of debris-coordinates distribution in the classification plane. The obtained results demonstrated a good availability for the automated wear particle analysis.

  • PDF

Nucleus Recognition of Uterine Cervical Pap-Smears using FCM Clustering Algorithm

  • Kim, Kwang-Baek
    • Journal of information and communication convergence engineering
    • /
    • 제6권1호
    • /
    • pp.94-99
    • /
    • 2008
  • Segmentation for the region of nucleus in the image of uterine cervical cytodiagnosis is known as the most difficult and important part in the automatic cervical cancer recognition system. In this paper, the region of nucleus is extracted from an image of uterine cervical cytodiagnosis using the HSI model. The characteristics of the nucleus are extracted from the analysis of morphemetric features, densitometric features, colormetric features, and textural features based on the detected region of nucleus area. The classification criterion of a nucleus is defined according to the standard categories of the Bethesda system. The fuzzy C-means clustering algorithm is employed to the extracted nucleus and the results show that the proposed method is efficient in nucleus recognition and uterine cervical Pap-Smears extraction.

Wear Debris Analysis using the Color Pattern Recognition

  • Chang, Rae-Hyuk;Grigoriev, A.Y.;Yoon, Eui-Sung;Kong, Hosung;Kang, Ki-Hong
    • KSTLE International Journal
    • /
    • 제1권1호
    • /
    • pp.34-42
    • /
    • 2000
  • A method and results of classification of four different metallic wear debris were presented by using their color features. The color image of wear debris was used far the initial data, and the color properties of the debris were specified by HSI color model. Particles were characterized by a set of statistical features derived from the distribution of HSI color model components. The initial feature set was optimized by a principal component analysis, and multidimensional scaling procedure was used fer the definition of a classification plane. It was found that five features, which include mean values of H and S, median S, skewness of distribution of S and I, allow to distinguish copper based alloys, red and dark iron oxides and steel particles. In this work, a method of probabilistic decision-making of class label assignment was proposed, which was based on the analysis of debris-coordinates distribution in the classification plane. The obtained results demonstrated a good availability for the automated wear particle analysis.

  • PDF

Non-destructive quality prediction of domestic, commercial red pepper powder using hyperspectral imaging

  • Sang Seop Kim;Ji-Young Choi;Jeong Ho Lim;Jeong-Seok Cho
    • Food Science and Preservation
    • /
    • 제30권2호
    • /
    • pp.224-234
    • /
    • 2023
  • We analyzed the major quality characteristics of red pepper powders from various regions and predicted these characteristics nondestructively using shortwave infrared hyperspectral imaging (HSI) technology. We conducted partial least squares regression analysis on 70% (n=71) of the acquired hyperspectral data of the red pepper powders to examine the major quality characteristics. Rc2 values of ≥0.8 were obtained for the ASTA color value (0.9263) and capsaicinoid content (0.8310). The developed quality prediction model was validated using the remaining 30% (n=35) of the hyperspectral data; the highest accuracy was achieved for the ASTA color value (Rp2=0.8488), and similar validity levels were achieved for the capsaicinoid and moisture contents. To increase the accuracy of the quality prediction model, we conducted spectrum preprocessing using SNV, MSC, SG-1, and SG-2, and the model's accuracy was verified. The results indicated that the accuracy of the model was most significantly improved by the MSC method, and the prediction accuracy for the ASTA color value was the highest for all the spectrum preprocessing methods. Our findings suggest that the quality characteristics of red pepper powders, even powders that do not conform to specific variables such as particle size and moisture content, can be predicted via HSI.

Estimation on Physical Habitat Suitability of Benthic Macroinvertebrates in the Hwayang Stream (화양천 저서성 대형무척추동물의 물리적 서식처 적합도 산정)

  • Kim, Ye Ji;Kong, Dongsoo
    • Journal of Korean Society on Water Environment
    • /
    • 제34권1호
    • /
    • pp.10-25
    • /
    • 2018
  • This study was conducted to estimate the habitat suitability of 17 benthic macroinvertebrate taxa in the Hwayang stream. Habitat Suitability Index (HSI) of benthic macroinvertebrates from the Hwayang stream was developed based on three physical habitat factors which include current velocity, water depth, and the substrate. The Weibull model was used as a probability density function to analyze the distribution of individual abundance by physical factors. The number of species and the total individual abundance increased along with the increase in current velocity. By means of Canonical Correspondence Analysis (CCA), the relative importance of each factor was determined in the following order: current velocity, water depth, and the mean diameter. The results depicted that, the most influential factor in the growth of benthic macroinvertebrates in the Hwavang system was current velocity. After comparing the analyzed results from the Hwayang stream with the resukts from the Gapyeong stream, the integrated HSI was drawn. The results indicated that current velocity and substrate had similar distributions of HSI in the two streams. This was due to the addition of unmeasured data from previous surveys, or the fact that benthic macroinvertebrates adapted to deeper waters in the Hwayang Stream. Most taxa showed a clear preference for a fast current velocity, deep water depth and coarse substrate except Baetiella, Epeorus, (mayflies), and Hydropsyche (caddisfly).

Real Time Traffic Signal Recognition Using HSI and YCbCr Color Models and Adaboost Algorithm (HSI/YCbCr 색상모델과 에이다부스트 알고리즘을 이용한 실시간 교통신호 인식)

  • Park, Sanghoon;Lee, Joonwoong
    • Transactions of the Korean Society of Automotive Engineers
    • /
    • 제24권2호
    • /
    • pp.214-224
    • /
    • 2016
  • This paper proposes an algorithm to effectively detect the traffic lights and recognize the traffic signals using a monocular camera mounted on the front windshield glass of a vehicle in day time. The algorithm consists of three main parts. The first part is to generate the candidates of a traffic light. After conversion of RGB color model into HSI and YCbCr color spaces, the regions considered as a traffic light are detected. For these regions, edge processing is applied to extract the borders of the traffic light. The second part is to divide the candidates into traffic lights and non-traffic lights using Haar-like features and Adaboost algorithm. The third part is to recognize the signals of the traffic light using a template matching. Experimental results show that the proposed algorithm successfully detects the traffic lights and recognizes the traffic signals in real time in a variety of environments.

Traffic Light and Speed Sign Recognition by using Hierarchical Application of Color Segmentation and Object Feature Information (색상분할 및 객체 특징정보의 계층적 적용에 의한 신호등 및 속도 표지판 인식)

  • Lee, Kang-Ho;Bang, Min-Young;Lee, Kyu-Won
    • The KIPS Transactions:PartB
    • /
    • 제17B권3호
    • /
    • pp.207-214
    • /
    • 2010
  • A method of the region extraction and recognition of a traffic light and speed sign board in the real road environment is proposed. Traffic light was recognized by using brightness and color information based on HSI color model. Speed sign board was extracted by measuring red intensity from the HSI color information We improve the recognition rate by performing an incline compensation of the speed sign for directions clockwise and counterclockwise. The proposed algorithm shows a robust recognition rate in the image sequence which includes traffic light and speed sign board.

Site Assessment Using Habitat Suitability Index for Manila Clam Ruditapes philippinarum in Geunso Bay Tidal Flats (서식지 적합지수를 이용한 근소만 갯벌 바지락(Ruditapes philippinarum)의 어장적지평가)

  • Choi, Yong-Hyeon;Hong, SokJin;Jeon, Seung-Ryul;Cho, Yoon-Sik
    • Korean Journal of Fisheries and Aquatic Sciences
    • /
    • 제52권5호
    • /
    • pp.511-518
    • /
    • 2019
  • Evaluating the habitat suitability of potential aquaculture sites for cultured species is critical to the sustainable use of tidal flats. This study evaluated the habitat suitability index (HSI) of 12 sites in a tidal flat aquaculture farm at Geunso Bay, Taean, in June 2016. The parameters used to model the suitability index were Growth (water temperature, chlorophyll ${\alpha}$, hydrodynamics), Survival (sediment-sand, mean size, air exposure), and Environment (DO, salinity). The HSI was calculated using weighted and No weighted geometric means. The results showed high habitat suitability at the bay's entrance (HIS; No weighted, 0.60-0.70; weighted, 0.60). Hydrodynamics, air exposure, sediment-sand and mean size are thought to have a significant impact on habitat selection by Manila clams Ruditapes philippinarum. This study explored the optimum habitat for Manila clams by calculating the HSI, providing basic data for tidal flat management.

Study of the Derive of Core Habitats for Kirengeshoma koreana Nakai Using HSI and MaxEnt (HSI와 MaxEnt를 통한 나도승마 핵심서식지 발굴 연구)

  • Sun-Ryoung Kim;Rae-Ha Jang;Jae-Hwa Tho;Min-Han Kim;Seung-Woon Choi;Young-Jun Yoon
    • Korean Journal of Environment and Ecology
    • /
    • 제37권6호
    • /
    • pp.450-463
    • /
    • 2023
  • The objective of this study is to derive the core habitat of the Kirengeshoma koreana Nakai utilizing Habitat Suitability Index (HSI) and Maximum Entropy (MaxEnt) models. Expert-based models have been criticized for their subjective criteria, while statistical models face difficulties in on-site validation and integration of expert opinions. To address these limitations, both models were employed, and their outcomes were overlaid to derive the core habitat. Five variables were identified through a comprehensive literature review and spatial analysis based on appearance coordinates. The environmental variables encompass vegetation zone, forest type, crown density, annual precipitation, and effective soil depth. Through surveys involving six experts, importance rankings and SI (Suitability Index) scores were established for each variable, subsequently facilitating the creation of an HSI map. Using the same variables, the MaxEnt model was also executed, resulting in a corresponding map, which was merged to construct the definitive core habitat map. Out of 16 observed locations of K. koreana, 15 were situated within the identified core habitat. Furthermore, an area historically known to host K. koreana but not verified in the present, Mt. Yeongchwi, was found to lack a core habitat. These findings suggest that the developed models exhibit a high degree of accuracy and effectively reflect the current ecological landscape.