Applied Graph Theory in Computer Vision and Pattern Recognition

This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.

Effect of cage type on the behaviour pattern of rabbit does at different physiological stages

Interest in commercially farmed rabbit welfare has increased in recent years. As a result, new alternative housing systems have been developed, although they require evaluation in order to demonstrate their potential for improving welfare. The aim of this trial was to study the behavioural traits of rabbit does housed in 2 different types of cage (TC): conventional vs. alternative with an elevated platform, at different physiological stages (PS); lactation and gestation. Behavioural observations were carried out on 12 rabbit commercial does using continuous 24 h video recording. Independently of PS and TC, rabbit does spent most of their time on foot mats (on av. 57.7%). However, due to the use of platforms (on av. 23.0% of time), lactating does spent 36.6% less time on foot mats (P<0.001) and gestating does spent 27.0% less time on wire mesh (P<0.001) in alternative cages than in conventional cages. Alternative cages allowed for standing posture, but this behaviour was only observed in gestating does (on av. 4.6 times a day). Frequency of drinking was higher in conventional than in alternative cages (24.6 vs. 19.1 times a day; P<0.05). Gestating does housed in conventional cages reached the highest duration and frequency of interacting with neighbours (276 s/d and 4.6 times/d; P<0.05). The frequency of interacting with kits was lower in alternative than in conventional cages (2.4 vs. 8.6 times a day; P<0.01). Doe behaviour was influenced by the time of day, with less activity during the midday hours. During dark hours, rabbit does more frequently performed restless behaviour such as hyperactivity or nursing, matching the time at which rabbit does spent more time on the platform. The platform was frequently used by rabbit does, regardless of their physiological stage, and during late lactation phase, when mothers were not receptive to nursing, does housed in alternative cages used the platform as a mean to flee from kits trying to suckle. Use of the platform might lead to hygienic problems due to retained faeces on the platform and faeces and urine falling onto animals located in the lower part of the cage. The absence of stereotypies in rabbit does of this trial, suggested that animal welfare was not compromised by the type of housing (conventional or alternative cages).

From residue matching patterns to protein folding topographies: General model and bovine pancreatic trypsin inhibitor

A coarse-grained model for protein-folding dynamics is introduced based on a discretized representation of torsional modes. The model, based on the Ramachandran map of the local torsional potential surface and the class (hydrophobic/polar/neutral) of each residue, recognizes patterns of both torsional conformations and hydrophobic-polar contacts, with tolerance for imperfect patterns. It incorporates empirical rates for formation of secondary and tertiary structure. The method yields a topological representation of the evolving local torsional configuration of the folding protein, modulo the basins of the Ramachandran map. The folding process is modeled as a sequence of transitions from one contact pattern to another, as the torsional patterns evolve. We test the model by applying it to the folding process of bovine pancreatic trypsin inhibitor, obtaining a kinetic description of the transitions between the contact patterns visited by the protein along the dominant folding pathway. The kinetics and detailed balance make it possible to invert the result to obtain a coarse topographic description of the potential energy surface along the dominant folding pathway, in effect to go backward or forward between a topological representation of the chain conformation and a topographical description of the potential energy surface governing the folding process. As a result, the strong structure-seeking character of bovine pancreatic trypsin inhibitor and the principal features of its folding pathway are reproduced in a reasonably quantitative way.

A Gene Coding for Tomato Fruit β-Galactosidase II Is Expressed during Fruit Ripening : Cloning, Characterization, and Expression Pattern

β-Galactosidases (EC 3.2.1.23) constitute a widespread family of enzymes characterized by their ability to hydrolyze terminal, nonreducing β-d-galactosyl residues from β-d-galactosides. Several β-galactosidases, sometimes referred to as exo-galactanases, have been purified from plants and shown to possess in vitro activity against extracted cell wall material via the release of galactose from wall polymers containing β(1→4)-d-galactan. Although β-galactosidase II, a protein present in tomato (Lycopersicon esculentum Mill.) fruit during ripening and capable of degrading tomato fruit galactan, has been purified, cloning of the corresponding gene has been elusive. We report here the cloning of a cDNA, pTomβgal 4 (accession no. AF020390), corresponding to β-galactosidase II, and show that its corresponding gene is expressed during fruit ripening. Northern-blot analysis revealed that the β-galactosidase II gene transcript was detectable at the breaker stage of ripeness, maximum at the turning stage, and present at decreasing levels during the later stages of normal tomato fruit ripening. At the turning stage of ripeness, the transcript was present in all fruit tissues and was highest in the outermost tissues (including the peel). Confirmation that pTomβgal 4 codes for β-galactosidase II was derived from matching protein and deduced amino acid sequences. Furthermore, analysis of the deduced amino acid sequence of pTomβgal 4 suggested a high probability for secretion based on the presence of a hydrophobic leader sequence, a leader-sequence cleavage site, and three possible N-glycosylation sites. The predicted molecular mass and isoelectric point of the pTomβgal 4-encoded mature protein were similar to those reported for the purified β-galactosidase II protein from tomato fruit.

The role of texture amplitude in shape from shading: evidence from a haptic matching task

The pattern of illumination on an undulating surface can be used to infer its 3-D form (shape from shading). But the recovery of shape would be invalid if the shading actually arose from reflectance variation. When a corrugated surface is painted with an albedo texture, the variation in local mean luminance (LM) due to shading is accompanied by a similar modulation in texture amplitude (AM). This is not so for reflectance variation, nor for roughly textured surfaces. We used a haptic matching technique to show that modulations of texture amplitude play a role in the interpretation of shape from shading. Observers were shown plaid stimuli comprising LM and AM combined in-phase (LM+AM) on one oblique and in anti-phase (LM-AM) on the other. Stimuli were presented via a modified ReachIN workstation allowing the co-registration of visual and haptic stimuli. In the first experiment, observers were asked to adjust the phase of a haptic surface, which had the same orientation as the LM+AM combination, until its peak in depth aligned with the visually perceived peak. The resulting alignments were consistent with the use of a lighting-from-above prior. In the second experiment, observers were asked to adjust the amplitude of the haptic surface to match that of the visually perceived surface. Observers chose relatively large amplitude settings when the haptic surface was oriented and phase-aligned with the LM+AM cue. When the haptic surface was aligned with the LM-AM cue, amplitude settings were close to zero. Thus the LM/AM phase relation is a significant visual depth cue, and is used to discriminate between shading and reflectance variations. [Supported by the Engineering and Physical Sciences Research Council, EPSRC].

Normal ECG Recognition for Express-Diagnostics Based on Scale-Space Representation and Dynamic Matching

A novel approach of normal ECG recognition based on scale-space signal representation is proposed. The approach utilizes curvature scale-space signal representation used to match visual objects shapes previously and dynamic programming algorithm for matching CSS representations of ECG signals. Extraction and matching processes are fast and experimental results show that the approach is quite robust for preliminary normal ECG recognition.

Handwritten and machine-printed text discrimination using a template matching approach

We propose a novel template matching approach for the discrimination of handwritten and machine-printed text. We first pre-process the scanned document images by performing denoising, circles/lines exclusion and word-block level segmentation. We then align and match characters in a flexible sized gallery with the segmented regions, using parallelised normalised cross-correlation. The experimental results over the Pattern Recognition & Image Analysis Research Lab-Natural History Museum (PRImA-NHM) dataset show remarkably high robustness of the algorithm in classifying cluttered, occluded and noisy samples, in addition to those with significant high missing data. The algorithm, which gives 84.0% classification rate with false positive rate 0.16 over the dataset, does not require training samples and generates compelling results as opposed to the training-based approaches, which have used the same benchmark.

QoE-aware power management in vehicle-to-grid networks:a matching-theoretic approach

Frequency, time and places of charging and discharging have critical impact on the Quality of Experience (QoE) of using Electric Vehicles (EVs). EV charging and discharging scheduling schemes should consider both the QoE of using EV and the load capacity of the power grid. In this paper, we design a traveling plan-aware scheduling scheme for EV charging in driving pattern and a cooperative EV charging and discharging scheme in parking pattern to improve the QoE of using EV and enhance the reliability of the power grid. For traveling planaware scheduling, the assignment of EVs to Charging Stations (CSs) is modeled as a many-to-one matching game and the Stable Matching Algorithm (SMA) is proposed. For cooperative EV charging and discharging in parking pattern, the electricity exchange between charging EVs and discharging EVs in the same parking lot is formulated as a many-to-many matching model with ties, and we develop the Pareto Optimal Matching Algorithm (POMA). Simulation results indicates that the SMA can significantly improve the average system utility for EV charging in driving pattern, and the POMA can increase the amount of electricity offloaded from the grid which is helpful to enhance the reliability of the power grid.

Percezione depth guidata mediante proiezione virtuale di pattern

L’utilizzo di informazioni di profondità è oggi di fondamentale utilità per molteplici settori applicativi come la robotica, la guida autonoma o assistita, la realtà aumentata e il monitoraggio ambientale. I sensori di profondità disponibili possono essere divisi in attivi e passivi, dove i sensori passivi ricavano le informazioni di profondità dall'ambiente senza emettere segnali, bensì utilizzando i segnali provenienti dall'ambiente (e.g., luce solare). Nei sensori depth passivi stereo è richiesto un algoritmo per elaborare le immagini delle due camere: la tecnica di stereo matching viene utilizzata appunto per stimare la profondità di una scena. Di recente la ricerca si è occupata anche della sinergia con sensori attivi al fine di migliorare la stima della depth ottenuta da un sensore stereo: si utilizzano i punti affidabili generati dal sensore attivo per guidare l'algoritmo di stereo matching verso la soluzione corretta. In questa tesi si è deciso di affrontare questa tematica da un punto di vista nuovo, utilizzando un sistema di proiezione virtuale di punti corrispondenti in immagini stereo: i pixel delle immagini vengono alterati per guidare l'algoritmo ottimizzando i costi. Un altro vantaggio della strategia proposta è la possibilità di iterare il processo, andando a cambiare il pattern in ogni passo: aggregando i passi in un unico risultato, è possibile migliorare il risultato finale. I punti affidabili sono ottenuti mediante sensori attivi (e.g. LiDAR, ToF), oppure direttamente dalle immagini, stimando la confidenza delle mappe prodotte dal medesimo sistema stereo: la confidenza permette di classificare la bontà di un punto fornito dall'algoritmo di matching. Nel corso della tesi sono stati utilizzati sensori attivi per verificare l'efficacia della proiezione virtuale, ma sono state anche effettuate analisi sulle misure di confidenza: lo scopo è verificare se le misure di confidenza possono rimpiazzare o assistere i sensori attivi.

Vascular Pattern In Enchondroma And Chondrosarcoma: Clinical And Immunohistologic Study.

Although cartilaginous tumors have low microvascular density, vessels are important for the provision of nutrition so that the tumor can grow and generate metastasis. The aim of this study was to assess the value of the vascular pattern classification as a prognostic tool in chondrosarcomas (CSs) and its relation with vascular endothelial growth factor (VEGF) expression. This was a retrospective study of 21 enchondromas and 57 conventional CSs. Clinical data and outcome were retrieved from medical files. CSs histologic grades (on a scale of 1 to 3) were determined according to the World Health Organization classification. The vascular pattern (on a scale of A to C) was assessed through CD34, according to Kalinski. CD105 and VEGF were also evaluated. Poor outcome was significantly associated with vascular pattern groups B and C. Higher vascular pattern were 6.5 times more frequent in moderate-grade and high-grade CSs than in grade 1 CS. On multivariate analysis, a clear correlation was found between VEGF overexpression and B/C vascular patterns. Only 18 (benign and malignant) tumors stained for CD105. The results point to the use of the vascular pattern classification as a prognostic tool in CSs and to differentiate low-grade from moderate-grade/high-grade CSs. Vascular pattern might be also used to complement histologic grade, VEGF immunostaining, and microvascular density, for indicating a patient's prognosis. Low-grade CSs develop under low neoangiogenesis, which conforms to the slow growth rate of these tumors.

Primary Relapse Site Pattern In Women With Triple-negative Breast Cancer.

Despite the remarkable improvements in breast cancer (BC) characterization, accurate prediction of BC clinical behavior is often still difficult to achieve. Some studies have investigated the association between the molecular subtype, namely the basal-like BC and the pattern of relapse, however only few investigated the association between relapse pattern and immunohistochemical defined triple-negative breast cancers (TNBCs). The aim of this study was to evaluate the pattern of relapse in patients with TNBC, namely the primary distant relapse site. One-hundred twenty nine (129) invasive breast carcinomas with follow-up information were classified according to the molecular subtype using immunohistochemistry for ER, PgR and Her2. The association between TNBC and distant relapse primary site was analyzed by logistic regression. Using multivariate logistic regression analysis patients with TNBC displayed only 0.09 (95% CI: 0.00-0.74; p=0.02) the odds of the non-TNBC patients of developing bone primary relapse. Regarding visceral and lymph-node relapse, no differences between in this cohort were found. Though classically regarded as aggressive tumors, TNBCs rarely development primary relapse in bone when compared to non-TNBC, a clinical relevant fact when investigating a metastasis of an occult or non-sampled primary BC.