A self-adaptive image processing application based on evolvable and scalable hardware

Evolvable Hardware (EH) is a technique that consists of using reconfigurable hardware devices whose configuration is controlled by an Evolutionary Algorithm (EA). Our system consists of a fully-FPGA implemented scalable EH platform, where the Reconfigurable processing Core (RC) can adaptively increase or decrease in size. Figure 1 shows the architecture of the proposed System-on-Programmable-Chip (SoPC), consisting of a MicroBlaze processor responsible of controlling the whole system operation, a Reconfiguration Engine (RE), and a Reconfigurable processing Core which is able to change its size in both height and width. This system is used to implement image filters, which are generated autonomously thanks to the evolutionary process. The system is complemented with a camera that enables the usage of the platform for real time applications.

Application of Improved Direct Calibration for Hyperspectral image processing: Detecting peanut traces in wheat flour.

NIR Hyperspectral imaging (1000-2500 nm) combined with IDC allowed the detection of peanut traces down to adulteration percentages 0.01% Contrary to PLSR, IDC does not require a calibration set, but uses both expert and experimental information and suitable for quantification of an interest compound in complex matrices. The obtained results shows the feasibility of using HSI systems for the detection of peanut traces in conjunction with chemical procedures, such as RT-PCR and ELISA

A Dynamically Adaptable Image Processing Application Trading Off Between High Performance, Consumption and Dependability in Real Time

As embedded systems evolve, problems inherent to technology become important limitations. In less than ten years, chips will exceed the maximum allowed power consumption affecting performance, since, even though the resources available per chip are increasing, frequency of operation has stalled. Besides, as the level of integration is increased, it is difficult to keep defect density under control, so new fault tolerant techniques are required. In this demo work, a new dynamically adaptable virtual architecture (ARTICo3) to allow dynamic and context-aware use of resources is implemented in a high performance Wireless Sensor node (HiReCookie) to perform an image processing application.

Methodology of image analysis for study of the vertisols moisture content

The main problem to study vertical drainage from the moisture distribution, on a vertisol profile, is searching for suitable methods using these procedures. Our aim was to design a digital image processing methodology and its analysis to characterize the moisture content distribution of a vertisol profile. In this research, twelve soil pits were excavated on a ba re Mazic Pellic Vertisols ix of them in May 13/2011 and the rest in May 19 /2011 after a moderate rainfall event. Digital RGB images were taken from each vertisol pit using a Kodak? camera selecting a size of 1600x945 pixels. Each soil image was processed to homogenized brightness and then a spatial filter with several window sizes was applied to select the optimum one. The RGB image obtained were divided in each matrix color selecting the best thresholds for each one, maximum and minimum, to be applied and get a digital binary pattern. This one was analyzed by estimating two fractal scaling exponents box counting dimension D BC) and interface fractal dimension (D) In addition, three pre-fractal scaling coefficients were determinate at maximum resolution: total number of boxes intercepting the foreground pattern (A), fractal lacunarity (?1) and Shannon entropy S1). For all the images processed the spatial filter 9x9 was the optimum based on entropy, cluster and histogram criteria. Thresholds for each color were selected based on bimodal histograms.

A study of feature combination for vehicle detection based on image processing

Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use of supervised classification approaches and resort to techniques, such as histograms of oriented gradients (HOG), principal component analysis (PCA), and Gabor filters, among others. Unfortunately, existing approaches are lacking in two respects: first, comparison between methods using a common body of work has not been addressed; second, no study of the combination potentiality of popular features for vehicle classification has been reported. In this study the performance of the different techniques is first reviewed and compared using a common public database. Then, the combination capabilities of these techniques are explored and a methodology is presented for the fusion of classifiers built upon them, taking into account also the vehicle pose. The study unveils the limitations of single-feature based classification and makes clear that fusion of classifiers is highly beneficial for vehicle verification.

Tag detection for preventing unauthorized face image processing

A new technology is being proposed as a solution to the problem of unintentional facial detection and recognition in pictures in which the individuals appearing want to express their privacy preferences, through the use of different tags. The existing methods for face de-identification were mostly ad hoc solutions that only provided an absolute binary solution in a privacy context such as pixelation, or a bar mask. As the number and users of social networks are increasing, our preferences regarding our privacy may become more complex, leaving these absolute binary solutions as something obsolete. The proposed technology overcomes this problem by embedding information in a tag which will be placed close to the face without being disruptive. Through a decoding method the tag will provide the preferences that will be applied to the images in further stages.

Image processing methods for human brain connectivity analysis from in-vivo diffusion MRI

The structural connectivity of the brain is considered to encode species-wise and subject-wise patterns that will unlock large areas of understanding of the human brain. Currently, diffusion MRI of the living brain enables to map the microstructure of tissue, allowing to track the pathways of fiber bundles connecting the cortical regions across the brain. These bundles are summarized in a network representation called connectome that is analyzed using graph theory. The extraction of the connectome from diffusion MRI requires a large processing flow including image enhancement, reconstruction, segmentation, registration, diffusion tracking, etc. Although a concerted effort has been devoted to the definition of standard pipelines for the connectome extraction, it is still crucial to define quality assessment protocols of these workflows. The definition of quality control protocols is hindered by the complexity of the pipelines under test and the absolute lack of gold-standards for diffusion MRI data. Here we characterize the impact on structural connectivity workflows of the geometrical deformation typically shown by diffusion MRI data due to the inhomogeneity of magnetic susceptibility across the imaged object. We propose an evaluation framework to compare the existing methodologies to correct for these artifacts including whole-brain realistic phantoms. Additionally, we design and implement an image segmentation and registration method to avoid performing the correction task and to enable processing in the native space of diffusion data. We release PySDCev, an evaluation framework for the quality control of connectivity pipelines, specialized in the study of susceptibility-derived distortions. In this context, we propose Diffantom, a whole-brain phantom that provides a solution to the lack of gold-standard data. The three correction methodologies under comparison performed reasonably, and it is difficult to determine which method is more advisable. We demonstrate that susceptibility-derived correction is necessary to increase the sensitivity of connectivity pipelines, at the cost of specificity. Finally, with the registration and segmentation tool called regseg we demonstrate how the problem of susceptibility-derived distortion can be overcome allowing data to be used in their original coordinates. This is crucial to increase the sensitivity of the whole pipeline without any loss in specificity.

Participation of the nuclear cap binding complex in pre-mRNA 3′ processing

Communication between the 5′ and 3′ ends is a common feature of several aspects of eukaryotic mRNA metabolism. In the nucleus, the pre-mRNA 5′ end is bound by the nuclear cap binding complex (CBC). This RNA–protein complex plays an active role in both splicing and RNA export. We provide evidence for participation of CBC in the processing of the 3′ end of the message. Depletion of CBC from HeLa cell nuclear extract strongly reduced the endonucleolytic cleavage step of the cleavage and polyadenylation process. Cleavage was restored by addition of recombinant CBC. CBC depletion was found to reduce the stability of poly(A) site cleavage complexes formed in nuclear extract. We also provide evidence that the communication between the 5′ and 3′ ends of the pre-mRNA during processing is mediated by the physical association of the CBC/cap complex with 3′ processing factors bound at the poly(A) site. These observations, along with previous data on the function of CBC in splicing, illustrate the key role played by CBC in pre-mRNA recognition and processing. The data provides further support for the hypothesis that pre-mRNAs and mRNAs may exist and be functional in the form of “closed-loops,” due to interactions between factors bound at their 5′ and 3′ ends.

Partially Processed pre-rRNA Is Preserved in Association with Processing Components in Nucleolus-derived Foci during Mitosis

Previous studies showed that components implicated in pre-rRNA processing, including U3 small nucleolar (sno)RNA, fibrillarin, nucleolin, and proteins B23 and p52, accumulate in perichromosomal regions and in numerous mitotic cytoplasmic particles, termed nucleolus-derived foci (NDF) between early anaphase and late telophase. The latter structures were analyzed for the presence of pre-rRNA by fluorescence in situ hybridization using probes for segments of pre-rRNA with known half-lives. The NDF did not contain the short-lived 5′-external transcribed spacer (ETS) leader segment upstream from the primary processing site in 47S pre-rRNA. However, the NDF contained sequences from the 5′-ETS core, 18S, internal transcribed spacer 1 (ITS1), and 28S segments and also had detectable, but significantly reduced, levels of the 3′-ETS sequence. Northern analyses showed that in mitotic cells, the latter sequences were present predominantly in 45S-46S pre-rRNAs, indicating that high-molecular weight processing intermediates are preserved during mitosis. Two additional essential processing components were also found in the NDF: U8 snoRNA and hPop1 (a protein component of RNase MRP and RNase P). Thus, the NDF appear to be large complexes containing partially processed pre-rRNA associated with processing components in which processing has been significantly suppressed. The NDF may facilitate coordinated assembly of postmitotic nucleoli.

Phosphoinositide Signaling Pathways in Nuclei Are Associated with Nuclear Speckles Containing Pre-mRNA Processing Factors

Phosphoinositide signal transduction pathways in nuclei use enzymes that are indistinguishable from their cytosolic analogues. We demonstrate that distinct phosphatidylinositol phosphate kinases (PIPKs), the type I and type II isoforms, are concentrated in nuclei of mammalian cells. The cytosolic and nuclear PIPKs display comparable activities toward the substrates phosphatidylinositol 4-phosphate and phosphatidylinositol 3-phosphate. Indirect immunofluorescence revealed that these kinases were associated with distinct subnuclear domains, identified as “nuclear speckles,” which also contained pre-mRNA processing factors. A pool of nuclear phosphatidylinositol bisphosphate (PIP2), the product of these kinases, was also detected at these same sites by monoclonal antibody staining. The localization of PIPKs and PIP2 to speckles is dynamic in that both PIPKs and PIP2 reorganize along with other speckle components upon inhibition of mRNA transcription. Because PIPKs have roles in the production of most phosphatidylinositol second messengers, these findings demonstrate that phosphatidylinositol signaling pathways are localized at nuclear speckles. Surprisingly, the PIPKs and PIP2 are not associated with invaginations of the nuclear envelope or any nuclear membrane structure. The putative absence of membranes at these sites suggests novel mechanisms for the generation of phosphoinositides within these structures.

Functional separation of pre-rRNA processing steps revealed by truncation of the U3 small nucleolar ribonucleoprotein component, Mpp10

The U3 small nucleolar ribonucleoprotein (snoRNP) is required for three cleavage events that generate the mature 18S rRNA from the pre-rRNA. In Saccharomyces cerevisiae, depletion of Mpp10, a U3 snoRNP-specific protein, halts 18S rRNA production and impairs cleavage at the three U3 snoRNP-dependent sites: A0, A1, and A2. We have identified truncation mutations of Mpp10 that affect 18S rRNA synthesis and confer cold-sensitivity and slow growth. However, distinct from yeast cells depleted of Mpp10, the mutants carrying these truncated Mpp10 proteins accumulate a novel precursor, resulting from cleavage at only A0. The Mpp10 truncations do not alter association of Mpp10 with the U3 snoRNA, nor do they affect snoRNA or protein stability. Thus, the role in processing of the U3 snoRNP can be separated into cleavage at the A0 site, which occurs in the presence of truncated Mpp10, and cleavage at the A1/A2 sites, which occurs only with intact Mpp10. These results strongly argue for a role for Mpp10 in processing at the A1/A2 sites.

RNA editing activity is associated with splicing factors in lnRNP particles: The nuclear pre-mRNA processing machinery

Multiple members of the ADAR (adenosine deaminases acting on RNA) gene family are involved in A-to-I RNA editing. It has been speculated that they may form a large multicomponent protein complex. Possible candidates for such complexes are large nuclear ribonucleoprotein (lnRNP) particles. The lnRNP particles consist mainly of four spliceosomal subunits that assemble together with the pre-mRNA to form a large particle and thus are viewed as the naturally assembled pre-mRNA processing machinery. Here we investigated the presence of ADARs in lnRNP particles by Western blot analysis using anti-ADAR antibodies and by indirect immunoprecipitation. Both ADAR1 and ADAR2 were found associated with the spliceosomal components Sm and SR proteins within the lnRNP particles. The two ADARs, associated with lnRNP particles, were enzymatically active in site-selective A-to-I RNA editing. We demonstrate the association of ADAR RNA editing enzymes with physiological supramolecular complexes, the lnRNP particles.

Image processing via level set curvature flow.

We present a controlled image smoothing and enhancement method based on a curvature flow interpretation of the geometric heat equation. Compared to existing techniques, the model has several distinct advantages. (i) It contains just one enhancement parameter. (ii) The scheme naturally inherits a stopping criterion from the image; continued application of the scheme produces no further change. (iii) The method is one of the fastest possible schemes based on a curvature-controlled approach.

Image processing for safety assessment in Civil Engineering

Behaviour analysis of construction safety systems is of fundamental importance to avoid accidental injuries. Traditionally, measurements of dynamic actions in Civil Engineering have been done through accelerometers, but high-speed cameras and image processing techniques can play an important role in this area. Here, we propose using morphological image filtering and Hough transform on high-speed video sequence as tools for dynamic measurements on that field. The presented method is applied to obtain the trajectory and acceleration of a cylindrical ballast falling from a building and trapped by a thread net. Results show that safety recommendations given in construction codes can be potentially dangerous for workers.

Trajectory-Based Morphological Operators: A Model for Efficient Image Processing

Mathematical morphology has been an area of intensive research over the last few years. Although many remarkable advances have been achieved throughout these years, there is still a great interest in accelerating morphological operations in order for them to be implemented in real-time systems. In this work, we present a new model for computing mathematical morphology operations, the so-called morphological trajectory model (MTM), in which a morphological filter will be divided into a sequence of basic operations. Then, a trajectory-based morphological operation (such as dilation, and erosion) is defined as the set of points resulting from the ordered application of the instant basic operations. The MTM approach allows working with different structuring elements, such as disks, and from the experiments, it can be extracted that our method is independent of the structuring element size and can be easily applied to industrial systems and high-resolution images.