Mean-Shift segmentation and PDE-based nonlinear diffusion: toward a common variational framework for foreground/background document image segmentation

Drira, Fadoua; Lebourgeois, Frank

doi:10.1007/s10032-017-0285-7

Cited by 5 publications

(2 citation statements)

References 43 publications

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“…Because noise-whether biological, mechanical, electrical, or digital-is a fundamental issue in communication, substantial research has aimed at improving document legibility by suppressing a great variety of what are usually considered manifestations of noise, including: ink bleed-through [46], see-through [48], foxing [163], shadows [95], termite bites [151], cross-outs [30], photocopied low-contrast carbon copies [36], low resolution raster images [141], and background texture interference [133] (for a history of image denoising, see [111]). The type of visual media can also dictate the typology of enhancement methods (e.g., methods for pictures and for movies differ in whether the time dimension is available as a source of contextual information for optimizing image processing) [24].…”

Section: Computer Science Researchmentioning

confidence: 99%

Personalizing image enhancement for critical visual tasks: improved legibility of papyri using color processing and visual illusions

Atanasiu

Marthot-Santaniello

2021

IJDAR

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This article develops theoretical, algorithmic, perceptual, and interaction aspects of script legibility enhancement in the visible light spectrum for the purpose of scholarly editing of papyri texts. Novel legibility enhancement algorithms based on color processing and visual illusions are compared to classic methods in a user experience experiment. (1) The proposed methods outperformed the comparison methods. (2) Users exhibited a broad behavioral spectrum, under the influence of factors such as personality and social conditioning, tasks and application domains, expertise level and image quality, and affordances of software, hardware, and interfaces. No single enhancement method satisfied all factor configurations. Therefore, it is suggested to offer users a broad choice of methods to facilitate personalization, contextualization, and complementarity. (3) A distinction is made between casual and critical vision on the basis of signal ambiguity and error consequences. The criteria of a paradigm for enhancing images for critical applications comprise: interpreting images skeptically; approaching enhancement as a system problem; considering all image structures as potential information; and making uncertainty and alternative interpretations explicit, both visually and numerically.

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Section: Computer Science Researchmentioning

confidence: 99%

Personalizing image enhancement for critical visual tasks: improved legibility of papyri using color processing and visual illusions

Atanasiu

Marthot-Santaniello

2021

IJDAR

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“…It aims at dividing an image into a series of non-overlapping image regions with similar characteristics such as spectral, texture, etc. Although many different kinds of methods have been proposed to solve this problem [1][2][3][4], it still keeps challenging because of noisy perturbation and low contrast of images.…”

Section: Introductionmentioning

confidence: 99%

An Automatic Fuzzy Image Segmentation Method Based on Wavelet Energy Histograms and Markov Random Field Models

Li¹,

Hong²

2017

dtetr

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Fuzzy C-Means (FCM) algorithm has been widely used in remote sensed image segmentation. However, it has two main defects: (1) its sensitiveness to noise outliers, and other imaging artifacts; (2) the number of clusters needed to be set previously. In order to overcome these problems, in this paper, we incorporate the wavelet energy histograms (WEHs) and Markov random field models (MRFs) into the fuzzy clustering procedure and present a novel image segmentation method. WEHs serve the determination of cluster centers and MRFs play a role of modelling spatial information. First of all, the peaks of wavelet histogram are exploited to find the initial cluster centers. Then, a fuzzy clustering procedure with MRFs is performed on each band separately. Finally, the fused label of the clustering result from each band is used as the final segmentation result. The superiority of the proposed method is demonstrated by comparing it with the some well-known methods of FCM, FLICM, HMRF-FCM, and AHFCM.

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Target detection in mine based on fusion of color and edge information

Xian

Jiang

2017

2017 International Conference on Advanced Mechatronic Systems (ICAMechS)

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Mean-Shift segmentation and PDE-based nonlinear diffusion: toward a common variational framework for foreground/background document image segmentation

Cited by 5 publications

References 43 publications

Personalizing image enhancement for critical visual tasks: improved legibility of papyri using color processing and visual illusions

Personalizing image enhancement for critical visual tasks: improved legibility of papyri using color processing and visual illusions

An Automatic Fuzzy Image Segmentation Method Based on Wavelet Energy Histograms and Markov Random Field Models

Target detection in mine based on fusion of color and edge information

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