• Title, Summary, Keyword: Bimodal Segmentation

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MOTION DETECTION USING CURVATURE MAP AND TWO-STEP BIMODAL SEGMENTATION

  • Lee, Suk-Ho
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.13 no.4
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    • pp.247-256
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    • 2009
  • In this paper, a motion detection algorithm which works well in low illumination environment is proposed. By using the level set based bimodal motion segmentation, the algorithm obtains an automatic segmentation of the motion region and the spurious regions due to the large CCD noise in low illumination environment are removed effectively.

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AUTOMATIC MOTION DETECTION USING FALSE BACKGROUND ELIMINATION

  • Seo, Jin Keun;Lee, Sukho
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.17 no.1
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    • pp.47-54
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    • 2013
  • This work deals with automatic motion detection for with surveillance tracking that aims to provide high-lighting movable objects which is discriminated from moving backgrounds such as moving trees, etc. For this aim, we perform a false background region detection together with an initial foreground detection. The false background detection detects the moving backgrounds, which become eliminated from the initial foreground detection. This false background detection is done by performing the bimodal segmentation on a deformed image, which is constructed using the information of the dominant colors in the background.

Application of Bimodal Histogram Method to Oil Spill Detection from a Satellite Synthetic Aperture Radar Image

  • Kim, Tae-Sung;Park, Kyung-Ae;Lee, Min-Sun;Park, Jae-Jin;Hong, Sungwook;Kim, Kum-Lan;Chang, Eunmi
    • Korean Journal of Remote Sensing
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    • v.29 no.6
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    • pp.645-655
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    • 2013
  • As one of segmentation techniques for Synthetic Aperture Radar (SAR) image with oil spill, we applied a bimodal histogram method to discriminate oil pixels from non-oil pixels. The threshold of each moving window was objectively determined using the two peaks in the histogram distribution of backscattering coefficients from ENVISAT ASAR image. To reduce the effect of wind speed on oil spill detection, we selected ASAR image which satisfied a limit of wind speeds for successful detection. Overall, a commonly used adaptive threshold method has been applied with a subjectively-determined single threshold. In contrast, the bimodal histogram method utilized herein produces a variety of thresholds objectively for each moving window by considering the characteristics of statistical distribution of backscattering coefficients. Comparison between the two methods revealed that the bimodal histogram method exhibited no significant difference in terms of performance when compared to the adaptive threshold method, except for around the edges of dark oil spots. Thus, we anticipate that the objective method based on the bimodality of oil slicks may also be applicable to the detection of oil spills from other SAR imagery.

Neighboring Elemental Image Exemplar Based Inpainting for Computational Integral Imaging Reconstruction with Partial Occlusion

  • Ko, Bumseok;Lee, Byung-Gook;Lee, Sukho
    • Journal of the Optical Society of Korea
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    • v.19 no.4
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    • pp.390-396
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    • 2015
  • We propose a partial occlusion removal method for computational integral imaging reconstruction (CIIR) based on the usage of the exemplar based inpainting technique. The proposed method is an improved version of the original linear inpainting based CIIR (LI-CIIR), which uses the inpainting technique to fill in the data missing region. The LI-CIIR shows good results for images which contain objects with smooth surfaces. However, if the object has a textured surface, the result of the LI-CIIR deteriorates, since the linear inpainting cannot recover the textured data in the data missing region well. In this work, we utilize the exemplar based inpainting to fill in the textured data in the data missing region. We call the proposed method the neighboring elemental image exemplar based inpainting (NEI-exemplar inpainting) method, since it uses sources from neighboring elemental images to fill in the data missing region. Furthermore, we also propose an automatic occluding region extraction method based on the use of the mutual constraint using depth estimation (MC-DE) and the level set based bimodal segmentation. Experimental results show the validity of the proposed system.

Stable Model for Active Contour based Region Tracking using Level Set PDE

  • Lee, Suk-Ho
    • Journal of information and communication convergence engineering
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    • v.9 no.6
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    • pp.666-670
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    • 2011
  • In this paper, we propose a stable active contour based tracking method which utilizes the bimodal segmentation technique to obtain a background color diminished image frame. The proposed method overcomes the drawback of the Mansouri model which is liable to fall into a local minimum state when colors appear in the background that are similar to the target colors. The Mansouri model has been a foundation for active contour based tracking methods, since it is derived from a probability based interpretation. By stabilizing the model with the proposed speed function, the proposed model opens the way to extend probability based active contour tracking for practical applications.

A Study of Digital Image Analysis of Chromatin Texture for Discrimination of Thyroid Neoplastic Cells (갑상선 종양세포 식별을 위한 염색질 텍스춰의 디지탈 화상해석에 관한 연구)

  • Juhng, Sang-Woo;Lee, Jae-Hyuk;Bum, Eun-Kyung;Kim, Chang-Won
    • The Korean Journal of Cytopathology
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    • v.7 no.1
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    • pp.23-30
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    • 1996
  • Chromatin texture, which partly reflects nuclear organization, is evolving as an important parameter indicating cell activation or transformation. In this study, chromatin pattern was evaluated by image analysis of the electron micrographs of follicular and papillary carcinoma cells of the thyroid gland and tested for discrimination of the two neoplasms. Digital grey images were converted from the electron micrographs, nuclear images, excluding nucleolus and intranuclear cytoplasmic inclusions, were obtained by segmentation; grey levels were standardized; and grey level histograms were generated. The histograms in follicular carcinoma showed Gaussian or near-Gaussian distribution and had a single peak, whereas those in papillary carcinoma had two peaks(bimodal), one at the black zone and the other at the white zone. In papillary carcinoma, the peak in the black zone represented an increased amount of heterochromatin particles and that at the white zone represented decreased electron density of euchromatin or nuclear matrix. These results indicate that the nuclei of follicular and papillary carcinoma cells differ in their chromatin pattern and the difference may be due to decondensed chromatin and/or matrix substances.

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