• 제목/요약/키워드: templates based image construction

검색결과 2건 처리시간 0.016초

화재상황에서 적용가능한 열화상 카메라의 파노라마 촬영을 위한 동일점 추출 알고리즘 (Image Matching Algorithm for Thermal Panorama Image Construction Adaptable for Fire Disasters)

  • 곽동기;김동환
    • 제어로봇시스템학회논문지
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    • 제22권11호
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    • pp.895-903
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    • 2016
  • In a fire disaster in a tunnel, people should be rescued immediately using the information obtained from cameras or sensors. However, in heavy smoke from a fire, people cannot be clearly identified by a mounted CCTV, which is only effective in a clear environment. A thermal camera can be an alternative to this in smoky situations and is capable of detecting people from their emitted thermal energy. On the other hand, the thermal image camera has a smaller field of view than an ordinary camera due to its lens characteristics and temperature error, etc. In order to cover a relatively wide area, panoramic image construction needs to be implemented. In this work, a template-based similarity matching algorithm for constructing the panorama image is proposed and its performance is verified through experiments. This scheme provides guidelines for coping with difficulty in image construction, which requires an exact correspondence search for two images in cases of heavy smoke.

New Cellular Neural Networks Template for Image Halftoning based on Bayesian Rough Sets

  • Elsayed Radwan;Basem Y. Alkazemi;Ahmed I. Sharaf
    • International Journal of Computer Science & Network Security
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    • 제23권4호
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    • pp.85-94
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    • 2023
  • Image halftoning is a technique for varying grayscale images into two-tone binary images. Unfortunately, the static representation of an image-half toning, wherever each pixel intensity is combined by its local neighbors only, causes missing subjective problem. Also, the existing noise causes an instability criterion. In this paper an image half-toning is represented as a dynamical system for recognizing the global representation. Also, noise is reduced based on a probabilistic model. Since image half-toning is considered as 2-D matrix with a full connected pass, this structure is recognized by the dynamical system of Cellular Neural Networks (CNNs) which is defined by its template. Bayesian Rough Sets is used in exploiting the ideal CNNs construction that synthesis its dynamic. Also, Bayesian rough sets contribute to enhance the quality of the halftone image by removing noise and discovering the effective parameters in the CNNs template. The novelty of this method lies in finding a probabilistic based technique to discover the term of CNNs template and define new learning rules for CNNs internal work. A numerical experiment is conducted on image half-toning corrupted by Gaussian noise.