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  • Open Access

    ARTICLE

    Defocus Blur Segmentation Using Local Binary Patterns with Adaptive Threshold

    Usman Ali, Muhammad Tariq Mahmood*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1597-1611, 2022, DOI:10.32604/cmc.2022.022219 - 03 November 2021

    Abstract Enormous methods have been proposed for the detection and segmentation of blur and non-blur regions of the images. Due to the limited available information about blur type, scenario and the level of blurriness, detection and segmentation is a challenging task. Hence, the performance of the blur measure operator is an essential factor and needs improvement to attain perfection. In this paper, we propose an effective blur measure based on local binary pattern (LBP) with adaptive threshold for blur detection. The sharpness metric developed based on LBP used a fixed threshold irrespective of the type and… More >

  • Open Access

    ARTICLE

    Fuzzy Based Hybrid Focus Value Estimation for Multi Focus Image Fusion

    Muhammad Ahmad1,*, M. Arfan Jaffar1, Fawad Nasim1, Tehreem Masood1, Sheeraz Akram2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 735-752, 2022, DOI:10.32604/cmc.2022.019691 - 03 November 2021

    Abstract

    Due to limited depth-of-field of digital single-lens reflex cameras, the scene content within a limited distance from the imaging plane remains in focus while other objects closer to or further away from the point of focus appear as blurred (out-of-focus) in the image. Multi-Focus Image Fusion can be used to reconstruct a fully focused image from two or more partially focused images of the same scene. In this paper, a new Fuzzy Based Hybrid Focus Measure (FBHFM) for multi-focus image fusion has been proposed. Optimal block size is very critical step for multi-focus image fusion.

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  • Open Access

    ARTICLE

    Defocus Blur Segmentation Using Genetic Programming and Adaptive Threshold

    Muhammad Tariq Mahmood*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4867-4882, 2022, DOI:10.32604/cmc.2022.019544 - 11 October 2021

    Abstract Detection and classification of the blurred and the non-blurred regions in images is a challenging task due to the limited available information about blur type, scenarios and level of blurriness. In this paper, we propose an effective method for blur detection and segmentation based on transfer learning concept. The proposed method consists of two separate steps. In the first step, genetic programming (GP) model is developed that quantify the amount of blur for each pixel in the image. The GP model method uses the multi-resolution features of the image and it provides an improved blur More >

  • Open Access

    ABSTRACT

    Superfast 3-D Shape Measurement with Binary Defocusing Techniques

    Song Zhang, Yajun Wang, Laura Ekstrand, Ying Xu, Yuanzheng Gong

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.18, No.2, pp. 39-40, 2011, DOI:10.3970/icces.2011.018.039

    Abstract High-speed, high-resolution 3-D shape measurement has become increasingly important, with broad applications including medicine, homeland security, and entertainment. Techniques such as structured light, stereovision, and LIDAR have led the way in this field. In recent years, we have made some progress, developing an unprecedented 60 Hz system utilizing a digital fringe projection and phase-shifting method and simultaneously achieving 40 Hz 3-D shape acquisition, reconstruction, and display. However, a conventional digital fringe projection system requires the computer to generate sinusoidal fringe patterns to be sent to the projector. Because 8 bits are usually needed to represent… More >

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