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An introduction to digital image processing
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The article was published on 1986-01-01 and is currently open access. It has received 1745 citations till now. The article focuses on the topics: Digital image processing & Image processing.read more
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Journal ArticleDOI
Extraction and recognition of artificial text in multimedia documents
TL;DR: An algorithm to localise artificial text in images and videos using a measure of accumulated gradients and morphological processing and a new technique for the binarisation of the text boxes based on a criterion maximizing local contrast is proposed.
Journal ArticleDOI
Previsual symptoms of Xylella fastidiosa infection revealed in spectral plant-trait alterations.
Pablo J. Zarco-Tejada,C. Camino,Pieter S. A. Beck,Ruth Sagardoy Calderón,Alberto Hornero,Alberto Hornero,Rocío Hernández-Clemente,Teja Kattenborn,Miguel Montes-Borrego,L. Susca,M. Morelli,Victoria González-Dugo,Peter North,Blanca B. Landa,Donato Boscia,Maria Saponari,Juan A Navas-Cortes +16 more
TL;DR: It is demonstrated that spectral plant-trait alterations caused by X. fastidiosa infection are detectable previsually at the landscape scale, a critical requirement to help eradicate some of the most devastating plant diseases worldwide.
Journal ArticleDOI
Periodic spotted patterns in semi-arid vegetation explained by a propagation-inhibition model
TL;DR: In this article, the propagation-inhibition (PI) model is used to predict that a periodic pattern characterized by a dominant wavelength can theoretically establish itself through a Turing-like spatial instability depending only on a trade-off between facilitative and competitive interactions among plants.
Posted Content
Automatic Pavement Crack Detection Based on Structured Prediction with the Convolutional Neural Network
TL;DR: A supervised method based on deep learning is proposed, which has the capability of dealing with different pavement conditions, and outperforms the existing methods with severely imbalanced data.
Journal ArticleDOI
Document binarization with automatic parameter tuning
TL;DR: An automatic technique for setting parameters in a manner that tunes them to the individual image, yielding a final binarization algorithm that can cut total error by one-third with respect to the baseline version is described.
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