215 research outputs found
An inpainting technique based on regularization to remove bleed-through from ancient documents
No full textIn the techniques proposed so far to remove bleed-through from digital images of ancient documents, two critical aspects are the identification of the occlusion areas, i.e. those pixels where the bleed-through pattern overlaps with the main foreground text, and the inpainting of the areas to be removed with a pattern that is in continuity with the surrounding background, often inhomogeneous due to paper texture or noise. In this paper we propose a new method for bleed-through removal that aims at solving both the aforementioned issues. The method first exploits information from the accurately registered images of the manuscript recto and verso to locate, in each side, the pixels corresponding to the interfering text, no matter if they are pure bleed-through or occlusion pixels. Then, processing separately the two sides, the identified areas are filled in by interpolating, through a suitable regularization model, the surrounding regions. We show the promising results obtained with this method on manuscripts affected by a very strong bleed-through
Demosaicing of noisy color images through edge-preserving regularization
No full textWe propose edge-preserving regularization for color image demosaicing in the realistic case of noisy data. We enforce both intrachannel local smoothness of the intensity, and interchannel local similarities of the edges. To describe these local correlations while preserving even the finest image details, we exploit suitable functions of the derivatives of first, second and third order. The solution of the demosaicing problem is defined as the minimizer of a non-convex energy function, accounting for all these constraints plus a data fidelity term. Minimization is performed via an iterative deterministic algorithm, applied to a family of approximating functions, each implicitly referring to meaningful discontinuities. Our method is irrespective of the specific color filter array employed. However, to permit quantitative comparisons with other published results, we tested it in the case of the Bayer CFA, and on the Kodak 24-image set
DROP SIZE DISTRIBUTION IN SPRAYS BY IMAGE-PROCESSING
No full textAn automatic analysis system has been developed and used to analyze photographs obtained by high-speed microphotography, the final aim being to derive spatial resolved size distributions of drops in sprays. The problem of determining whether photographic images of particles are in focus or not is solved by obtaining a calibration of geometric parameters of particle images as functions both of the particle position in the camera's field of view and of the particle diameter. On the basis of the results of this calibration on the particular photographic system being used, the drops are automatically rejected or sized and counted. This is done through a procedure based on the geometrical characterization of drop images at different ranges of gray levels. The main body of such procedure is constituted by an algorithm of original design (connected components detection algorithm) which allows for the simultaneous detection of the boundaries of drop images at different gray levels and generates a hierarchical structure among them. Size distributions obtained by means of the procedure described in the paper offer significant reduction in experimental time as well as improvement in experimental accuracy, in relation to manual sizing and counting techniques
Giusti L, Baldini C, Bazzichi L, Ciregia F, Tonazzini I, Mascia G, Giannaccini G, Bombardieri S, Lucacchini A
No full textMultichannel Blind Separation and Deconvolution of Images for Document Analysis
No full textIn this paper, we apply Bayesian blind source separation (BSS) from noisy convolutive mixtures to jointly separate and restore source images degraded through unknown blur operators, and then linearly mixed. We found that this problem arises in several image processing applications, among which there are some interesting instances of degraded document analysis. In particular, the convolutive mixture model is proposed for describing multiple views of documents affected by the overlapping of two or more text patterns. We consider two different models, the interchannel model, where the data represent multispectral views of a single-sided document, and the intrachannel model, where the data are given by two sets of multispectral views of the recto and verso side of a document page. In both cases, the aim of the analysis is to recover clean maps of the main foreground text, but also the enhancement and extraction of other document features, such as faint or masked patterns. We adopt Bayesian estimation for all the unknowns and describe the typical local correlation within the individual source images through the use of suitable Gibbs priors, accounting also for well-behaved edges in the images. This a priori information is particularly suitable for the kind of objects depicted in the images treated, i.e., homogeneous texts in homogeneous background, and, as such, is capable to stabilize the ill-posed, inverse problem considered. The method is validated through numerical and real experiments that are representative of various real scenarios
An Extended Maximum Likelihood Approach for the Robust Blind Separation of Autocorrelated Images from Noisy Mixtures
No full textControllable Multibending Soft Actuator for Surgical Applications
No full textSoft actuators offer great versatility in terms of design and applications. Their compliance affords them greater dexterity as compared to rigid structures, and also permits the possibility to adapt their shape as per need. However compliance makes it difficult for them to sustain loads. As a step towards resolving this conundrum, a low melting point alloy based stiffening methodology is proposed to be integrated with a soft actuator designed for minimally invasive surgical use. This integration not only increases the load capacity but also helps motion control by selectively rigidifying parts of the actuator. The actuator design may be tweaked by using FEM based models, with a possibility to increase the overall stiffness up to 30 times
An Edge-Preserving Regularization Model for the Demosaicing of Noisy Color Images
No full textThis paper proposes an edge-preserving regularization technique to solve the color image demosaicing problem in the
realistic case of noisy data. We enforce intra-channel local smoothness of the intensity (low-frequency components) and
inter-channel local similarity of the depth of object borders and textures (high-frequency components). Discontinuities of
both the low-frequency and high-frequency components are accounted for implicitly, i.e., through suitable functions of the
proper derivatives. For the treatment of even the finest image details, derivatives of first, second, and third orders are considered.
The solution to the demosaicing problem is defined as theminimizer of an energy function, accounting for all these constraints
plus a data fidelity term. This non-convex energy is minimized via an iterative deterministic algorithm, applied to a family of
approximating functions, each implicitly referring to geometrically consistent image edges. Our method is general because
it does not refer to any specific color filter array. However, to allow quantitative comparisons with other published results,
we tested it in the case of the Bayer CFA and on the Kodak 24-image dataset, the McMaster (IMAX) 18-image dataset,
the Microsoft Demosaicing Canon 57-image dataset, and the Microsoft Demosaicing Panasonic 500-image dataset. The
comparisons with some of the most recent demosaicing algorithms show the good performance of our method in both the
noiseless and noisy cases
Study of adhesion and migration dynamics in ubiquitin E3A ligase (UBE3A)-silenced SYSH5Y neuroblastoma cells by micro-structured surfaces
No full textDuring neuronal development, neuronal cells read extracellular stimuli from the micro/nano-environment within which they exist, retrieving essential directionality and wiring information. Here, focal adhesions (FAs-protein clusters anchoring integrins to cytoskeleton) act as sensors, by integrating signals from both the extracellular matrix environment and chemotactic factors, contributing to the final neuronal pathfinding and migration. In the processes that orchestrate neuronal development, the important function of ubiquitin E3A ligase (UBE3A) is emerging. UBE3A has crucial functions in the brain and changes in its expression levels lead to neurodevelopmental disorders: the lack of UBE3A leads to Angelman syndrome (AS, OMIN 105830), while its increase causes autisms (Dup15q-autism). By using nano/micro-structured anisotropic substrates we previously showed that UBE3A-deficient neurons have deficits in contact guidance (Tonazzini et al, Mol Autism 2019). Here, we investigate the adhesion and migration dynamics of UBE3A-silenced SH-SY5Y neuroblastoma cells in vitro by exploiting nano/micro-grooved substrates. We analyze the molecular processes regulating the development of FAs by transfection with EGFP-vector encoding for paxillin, a protein of FA clusters, and by live-cell total-internal-reflection-fluorescence microscopy. We show that UBE3A-silenced SH-SY5Y cells have impaired FA morphological development and pathway activation, which lead to a delayed adhesion and also explain the defective contact guidance in response to directional topographical stimuli. However, UBE3A-silenced SH-SY5Y cells show an overall normal migration behavior, in terms of speed and ability to follow the GRs directional stimulus. Only the collective cell migration upon cell gaps was slightly delayed for UBE3Ash SHs. Overall, the deficits of UBE3Ash SHS-SY5Y cells in FA maturation/sensing and in collective migration may have patho-physiological implications, in AS condition, considering the much more complex stimuli that neurons find in vivo during the neurodevelopment
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