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We developed a method of image preprocessing based on the information entropy, namely, on the information contribution made by each individual pixel to the whole image or to image’s part (i.e., a Point Information Gain; PIG). An idea of the PIG calculation is that an image background remains informatively poor, whereas objects carry relevant information. In one calculation, this method preserves details, highlights edges, and decreases random noise. This paper describes optimization and implementation of the PIG calculation on graphical processing units (GPU) to overcome a high computational burden.

High rates of progestins consumption in the form of active ingredients in women's oral contraceptives and other hormonal preparations may lead to their increased concentrations in aquatic environments and subsequent harmful effect on fish reproduction. The objective of the present study was to assess the effect of etonogestrel, a third-generation synthetic progestin, on the reproductive behavior, fertility, gonads histology, and secondary sexual characteristics of male and female Endler's guppies (Poecilia wingei). Fish were subjected for 34 days to two concentrations of etonogestrel, including one possibly environmentally relevant (3.2 ng L−1) and one sublethal (320 ng L−1) concentration. A mating behavior study was subsequently conducted and revealed that the treatment with etonogestrel significantly reduced mating frequency in the exposed fish compared to controls. All the exposed females were unable to reproduce. In addition, female fish exposed to the highest level of etonogestrel were masculinized, as their anal fins and body coloration showed patterns similar to those of male fish. Etonogestrel-exposed females also had fewer developed oocytes. In conclusion, the low etonogestrel concentration (3.2 ng L−1) led to a reduction of mating activity in males without effect on their reproductive success, but it completely inhibited reproduction in females. Exposure to etonogestrel clearly has more severe consequences for females than males.

The precision fish farming concept has been widely investigated in research and is highly desirable in aquaculture as it creates opportunities for precisely controlling and monitoring fish cultivation processes and increasing fish welfare. The automatic identification of individual fish could be one of the keys to enabling individual fish treatment. In a previous study, we already demonstrated that the visible patterns on a fish’s body can be used for the non-invasive individual identification of fishes from the same species (with obvious skin patterns, such as salmonids) over long-term periods. The aim of this study was to verify the possibility of using fully-automatic non-invasive photo-identification of individual fish based on natural marks on the fish’s body without any obvious skin patterns. This approach is an alternative to stressful invasive tagging and marking techniques. Scale patterns on the body and operculum, as well as lateral line shapes, were used as discriminative features for the identification of individuals in a closed group of fish. We used two fish species: the European seabass Dicentrarchus labrax and the common carp Cyprinus carpio. The identification method was tested on four experimental data sets for each fish species: two separate short-term data sets (pattern variability test) and two long-term data sets (pattern stability test) for European seabass (300 individual fish) and common carp (32 individual fish). The accuracy of classification was 100% for both fish species in both the short-term and long-term experiments. According to these results, the methods used for automatic non-invasive image-based individual-fish identification can also be used for fish species without obvious skin patterns.

International audience; Crayfish are widely used as a bioindicator of water pollution levels and as a model organism to study environmental changes. Existing non-invasive systems for water pollution detection using the crayfish use the optical principle of heart rate monitoring. The aim of this study is to develop an alternative method to crayfish heart rate monitoring which solves the problems associated with the current methods. The introduced solution is based on the use of crayfish vibration measurement using an accelerometer. The method enables us to determine the heart rate and provide a quantitively similar signal to the existing systems. The advantage of this method is the direct detection of crayfish locomotor activity from a signal measured by one sensor only; optical sensors require an additional sensor for crayfish motion detection. The method is an alternative to the existing methods for water pollution detection and ethological experiments.

Methamphetamine (METH), a central nervous system stimulant used as a recreational drug, is frequently found in surface waters at potentially harmful concentrations. To determine effects of long-term exposure to environmentally relevant levels on nontarget organisms, we analysed cardiac and locomotor responses of signal crayfish Pacifastacus leniusculus to acute stress during a 21-day exposure to METH at 1 &mu, g L&minus, 1 followed by 14 days depuration. Heart rate and locomotion were recorded over a period of 30 min before and 30 min after exposure to haemolymph of an injured conspecific four times during METH exposure and four times during the depuration phase. Methamphetamine-exposed crayfish showed a weaker cardiac response to stress than was observed in controls during both exposure and depuration phases. Similarly, methamphetamine-exposed crayfish, during METH exposure, showed lower locomotor reaction poststressor application in contrast to controls. Results indicate biological alterations in crayfish exposed to METH at low concentration level, potentially resulting in a shift in interactions among organisms in natural environment.

Methamphetamine (METH), a central nervous system stimulant used as a recreational drug, is frequently found in surface waters at potentially harmful concentrations. To determine effects of long-term exposure to environmentally relevant levels on nontarget organisms, we analysed cardiac and locomotor responses of signal crayfish Pacifastacus leniusculus to acute stress during a 21-day exposure to METH at 1 μg L−1 followed by 14 days depuration. Heart rate and locomotion were recorded over a period of 30 min before and 30 min after exposure to haemolymph of an injured conspecific four times during METH exposure and four times during the depuration phase. Methamphetamine-exposed crayfish showed a weaker cardiac response to stress than was observed in controls during both exposure and depuration phases. Similarly, methamphetamine-exposed crayfish, during METH exposure, showed lower locomotor reaction poststressor application in contrast to controls. Results indicate biological alterations in crayfish exposed to METH at low concentration level, potentially resulting in a shift in interactions among organisms in natural environment.

The classification of the fish silhouettes allows a quick decision of the fish species presence and amount in the given scene. The classical approach of the machine learning is used to test the question of linear separability of fish species silhouettes classes. The preprocessing of images consisted of object to background segmentation and image registration. The classificator is trained using modified Rosenblatt algorithm for loss function of discriminant analysis.

Fish feed delivery is one of the challenges which fish farmers encounter daily. The main aim of the feeding process is to ensure that every fish is provided with sufficient feed to maintain desired growth rates. The properties of fish feed pellet, such as water stability, degree of swelling or floating time, are critical traits impacting feed delivery. Some considerable effort is currently being made with regard to the replacement of fish meal and fish oil with other sustainable alternative raw materials (i.e., plant or insect-based) with different properties. The main aim of this study is to investigate the motion and residence time distribution (RTD) of two types of solid feed pellets with different properties in a cylindrical fish tank. After experimental identification of material and geometrical properties of both types of pellets, a detailed 3D computational fluid dynamics (CFD) study for each type of pellets is performed. The mean residence time of pellets injected at the surface of the fish tank can differ by up to 75% depending on the position of the injection. The smallest residence time is when the position is located at the center of the liquid surface (17 s); the largest is near the edge of the tank (75 s). The maximum difference between the two studied types of pellets is 25% and it increases with positions closer to the center of the tank. The maximum difference for positions along the perimeter at 3/4 tank radius is 8%; the largest residence times are observed at the opposite side of the water inlet. Based on this study, we argue that the suitability of different solid feed pellets for aquaculture systems with specific fish can be determined, and eventually the pellet composition (formula) as well as the injection position can be optimized.

Fish size and mass information during different growth stages is important for precise feeding regime management, oxygen consumption calculations, antibiotic prescription and improving fish welfare, but also to facilitate decisions on grading, harvesting and time to harvest. The main purpose of this study was to develop an automatic system to estimate fish mass using fish dorsal geometrical features and machine learning algorithms such as random forest (RF) and support vector machine (SVM). To develop the model, Kinect as a RGB-D camera was used to acquire depth map and top view images of 295 farmed seabass (Dicentrarchus labrax, L.) of different sizes. Eight dorsal geometric features were extracted and used for model development. Ten-fold cross validation was used to optimize and validate the models. Comparison of models was made in term of the coefficient of determination ( R cv 2 ) and Root Mean Square Error of prediction (RMSEP) of cross validation. Both models exhibited significant prediction, however, SVM algorithm with R cv 2 of 0.872 (p R cv 2 of 0.868 (p R 2 = 0.84 p 0.01 and RMSE = 0.12 was better in comparison to SVM with R 2 = 0.72 ( p 0.01 ) and RMSE = 0.16. The study demonstrated that seabass geometrical dorsal features together with machine learning algorithms could be used for mass predictions. Furthermore, the IREF system can be used as a reliable, inexpensive, stress-free and accurate sensor for monitoring and estimating fish mass during cultivation within the tank.

The crayfish is widely accepted as very sensitive and fast bio-indicator of changes in water quality. Studies based on heart beat analysis demonstrated the potential of using crayfish as a detector of pollutants consequently several computer-aided systems were developed to use this mechanism. The main complication with applying such a system is the necessity of using metal wires or optical fibres to transmit the signal from sensor which is placed on back of the crayfish to the processing hardware; these attachments restrict system design to one crayfish in one aquarium. We introduced an original system for crayfish heart beat monitoring based on completely non-invasive/contactless hardware. The system can determine crayfish heart beat frequency using only the combination of near infra-red (NIR) illuminator and sensitive camera. The heart rate is the only parameter needed in most of the studies using crayfish as a bio-indicator. We developed the system which needs no attachment, so more crayfish in one aquarium can be monitored simultaneously and it provides accurate information on heart rate and crayfish need no adaptation to the system. It can be used as equivalent to existing systems to simplify the crayfish studies.

In this study, cardiac and locomotor activities of signal crayfish Pacifastacus leniusculus were investigated under exposure to a range of natural (i.e., odors of conspecific crayfish, predatory fish, food, and injured conspecific) and one chemical (i.e., disinfectant chloramine-T) stimuli. Crayfish locomotion was simultaneously initiated with an increase in heart rate only when affected by chloramine-T, while locomotor response was delayed in all cases (or was not manifested at all by some specimens) when disturbed by the natural stressors. The heart rate differences measured before and during the stimulation were arranged as follows: odor of conspecific crayfish (9.2 ± 7.1%)

Simple Summary Restocking programmes are of crucial importance for the stabilisation of wild sturgeon stocks. Despite massive restocking, the survival rate of post-released fish is very low. The low survival is most likely caused by poor fish adaptability due to hatchery rearing practices. This study aimed to provide a deeper understanding of the effect of different feeding applications with day and night regimes and periods of starvation on the modified swimming behaviour of Siberian sturgeons reared in recirculating aquaculture conditions. Our data showed that the modified behaviour of the Siberian sturgeon in our study was caused by fish starvation rather than by the method of feed application or day/night light regimes. Abstract Restocking programmes of different fish species have been implemented worldwide. However, the survival of hatchery-reared fish after release to riverine ecosystems is at a very low level. One of the reasons for the high mortality rate of post-released fish is their modified swimming behaviour due to the hatchery rearing practice. To investigate one of the possible causes for modified swimming behaviour, Acipenser baerii larvae were exposed to surface- and bottom-feeding applications with day and night light regimes in a factorial design. We also analysed the effect of 5 and 10 days of starvation after different feeding applications on sturgeon swimming behaviour. The surface-feeding application was previously expected to promote the frequent Siberian sturgeon swim up to the mid- and top-water layers in our rearing facilities. However, our results indicated that the modified behaviour of the Siberian sturgeon in our study was caused by fish starvation and a possible predator-free environment rather than by the method of feed application or the day/night light regimes. These results may be used to improve the implementation of restocking programmes either through modified hatchery rearing practice or the training of foraging skills with predator stimuli.

This study focuses on the use of crayfish as bioindicators in the water treatment process during operating conditions. The crayfish physiological responses to water disinfected with chlorine dioxide (ClO2) was evaluated. Monitoring was conducted at the private commercial enterprise Protiv&iacute, n Brewery in Czech Republic under standard operating conditions. This brewery has a water treatment facility, where ClO2 is used for water purification. A total of 25 adult signal crayfish (Pacifastacus leniusculus) were kept in separate flow-through aquaria receiving the purified water with ClO2 concentrations ranging from 0.01 to 0.29 mg L&minus, 1. Diurnal rhythms of 32% of crayfish was disturbed even at lower concentrations of ClO2 (0.01&ndash, 0.2 mg L&minus, 1), while higher concentrations (&gt, 1) affected all animals. A random decline and rise of heart rate was detected. In addition, the frequent occurrence of higher levels of ClO2 significantly increased mortality. On average, mortality of crayfish occurred three to four weeks after stocking into the experimental system. Crayfish mortality is estimated to occur at concentrations exceeding 0.2 mg L&minus, 1 of ClO2. Our results suggest that long-term exposure to ClO2 adversely affects crayfish physiology. In addition, the results of this study could contribute to the use of crayfish as bioindicators in long-term water quality monitoring under industrial conditions.

Evidence of the ecological and biological impact of pharmaceuticals in surface waters on aquatic organisms is increasing. Tramadol is a synthetic opioid analgesic used to treat chronic and acute pain. To investigate its long-term effects at environmentally relevant levels, we evaluated heart rate (HR) and locomotion of signal crayfish Pacifastacus leniusculus during a 21-day exposure to 1 μg L-1 tramadol followed by 14 days depuration. Locomotion and HR were recorded over a period 30 min before and 30 min after exposure to physiological fluids of an injured conspecific, a natural stressor, four times during the tramadol exposure and four times during depuration. A significant increase in HR following stress induction was found in the majority of tramadol-exposed and control crayfish, as well as significant group-specific HR changes between both groups. Locomotor activity during tramadol treatment differed from that during depuration, in general showing less time spent in locomotion and lower distance moved. The tramadol exposed crayfish exhibited higher velocity during depuration than during the exposure period. Results may suggest a potential shift in prey-predator relationships.

A crayfish is a pivotal aquatic organism that serves both as a practical biological model for behavioral and physiological studies of invertebrates and as a useful biological indicator of water quality. Even though crayfish cannot directly specify the substances that cause water quality deterioration, they can immediately (within a few seconds) warn humans of water quality deterioration via acute changes in their cardiac and behavioral activities. In this study, we present a noninvasive method that is simple enough to be implemented under various conditions due to a combination of simplicity and reliability in one model. This approach, in which the biological organisms are implemented into environmental evaluation processes, provides a reliable and timely alarm for warning of and preventing acute water deterioration in an ambient environment. Therefore, this noninvasive system based on crayfish physiological and ethological parameter recordings was investigated for the detection of changes in an aquatic environment. This system is now applied at a local brewery for controlling quality of the water used for beverage production, but it can be used at any water treatment and supply facility for continuous, real-time water quality evaluation and for regular laboratory investigations of crayfish cardiac physiology and behavior.

This article is summarizing the general subtask pipeline during the processing and analysis of electron microscopy images. The overview is going from data acquisition, through noise description, filtration, segmentation, to detection. There are emphasized the difference from the expected conditions in macro-world imaging. The illustrative parameterization and statistical classification are explained on the immunolabeling example.

The observation of the nano sized objects in electron microscopy is demanding an automation of evaluation of captured images. The analysis of the digital images should be focused on objects detection, classification, and parametrization. In this work, three different examples of bioinformatical tasks are presented and discussed. The sphericity of such objects is one of the key parameter in nano object detections. The parametrization has to deal with specific properties of electron microscopy images, like high level of noise, low contrast, uneven background, and few pixels per objects. The presented approach combines unsupervised filtration and automatic object detection. The result is the software application with simple graphic user interface.

Many fish rearing infrastructures are already equipped with human-operated camera systems for fish behavior monitoring, e.g. for stopping the feeding system when the fish is satiated or for monitoring of fish behavior abnormalities caused by poor water quality or diseases. The novel infrared reflection (IREF) system for indoor 3D tracking of fish demonstrated in the current study allows for automation of fish behavior monitoring, reducing the system running costs by eliminating the need for continuous human monitoring and increasing the behavioral analysis accuracy by excluding the human subjectivity factor. The operating principle of this system is based on the effect of strong absorption of near infrared (NIR) range light by water, thus allowing estimation of fish distance based on the corresponding fish object brightness on the camera image. The use of NIR illuminator as a part of the IREF system allows fish behavior monitoring in the dark so as not to affect fish circadian rhythm. A system evaluation under aquaculture facility conditions with Atlantic salmon ( Salmo salar ) using flow-through water in tanks, showed the mean depth estimation error was equal to 5.3 ± 4.0 (SD) cm. The physiological variations among conspecific individual fish introduced the mean depth estimation error of 1.6 ± 1.3 (SD) cm. The advantages of the IREF system over well-known stereo vision systems are lower hardware cost and less computationally intensive 3D coordinates estimation algorithm, while the disadvantage is lower accuracy that is nevertheless acceptable for most applications of aquaculture fish monitoring.

Bioimaging, image segmentation, thresholding, and multivariate processing are helpful tools in analysis of series of images from many time lapse experiments. The different methods of mathematic, algorithmization and artificial intelligence could by modified, parametrized or adopted for single purpose case of completely different biological background (namely microorganisms, tissue cultures, aquaculture). However, most of the task is based on initial image segmentation, before features axtraction and comparison tasks are evaluated. In this article, we compare several of classical approaches in bioinformatical and biophysical cases with the neural network approach. The concept of neural network was adopted from the biological neural networks. Th networks need to be trained, however after the learning phase, they should be able to find one solution for various objects. The comparison of the methods is evaluated via error in segmentation according to the human supervisor.

Crayfish cardiac activity monitoring and analysis are widely used during water pollution and ethological studies. A noninvasive crayfish cardiac activity monitoring (NICCAM) system discussed in the current study permits long-term, continuous monitoring of several crayfish simultaneously. The advantages of the system are low price, low number of required components and the possibility of cardiac signal shape monitoring. Calculation and analysis of parameters characterizing the shape of the double peak cardiac activity allows not only reducing the number of incorrect peak detections improving the system accuracy but also can provide additional information on crayfish state. The discussed preliminary experiments on the effect of food odor and chloramine-T on crayfish showed promising potential of signal shape analysis for studying of crayfish cardiac reaction to changes in the aquatic environment.

Biocompatibility testing of new materials is often performed in vitro by measuring the growth rate of mammalian cancer cells in time-lapse images acquired by phase contrast microscopes. The growth rate is measured by tracking cell coverage, which requires an accurate automatic segmentation method. However, cancer cells have irregular shapes that change over time, the mottled background pattern is partially visible through the cells and the images contain artifacts such as halos. We developed a novel algorithm for cell segmentation that copes with the mentioned challenges. It is based on temporal differences of consecutive images and a combination of thresholding, blurring, and morphological operations. We tested the algorithm on images of four cell types acquired by two different microscopes, evaluated the precision of segmentation against manual segmentation performed by a human operator, and finally provided comparison with other freely available methods. We propose a new, fully automated method for measuring the cell growth rate based on fitting a coverage curve with the Verhulst population model. The algorithm is fast and shows accuracy comparable with manual segmentation. Most notably it can correctly separate live from dead cells.

Freshwater biodiversity is globally threatened by various factors while severe weather events like long-term droughts may be substantially devastating. In order to remain in contact with the water or stay in a sufficiently humid environment at drying localities, the ability to withstand desiccation by dwelling in the hyporheic zone, particularly through vertical burrowing is crucial. We assessed the ability of three European native and five non-native crayfish as models to survive and construct vertical burrows in a humid sandy-clayey substrate under a simulated one-week drought. Three native species (Astacus astacus, A. leptodactylus and Austropotamobius torrentium) suffered extensive mortalities. Survival of non-native species was substantially higher while all specimens of Cherax destructor and Procambarus clarkii survived. The native species and Pacifastacus leniusculus exhibited no ability to construct vertical burrows. Procambarus fallax f. virginalis and P. clarkii constructed bigger and deeper burrows than C. destructor and Orconectes limosus. In the context of predicted weather fluctuations, the ability to withstand desiccation through constructing vertical burrows into the hyporheic zone under drought conditions might play a significant role in the success of particular crayfish species, as well as a wide range of further hyporheic-dwelling aquatic organisms in general.

The article demonstrates the most frequent mistakes made upon the transformation of digital images in biology. An image is formed by a few physical processes which contribute to each color channel in a different way. In the case of microscopic image in transmitting light, these processes are mainly light diffraction and absorption and autofluorescence of objects, which are all followed by distortion of wavefronts by the microscope optics. The final image is then a result of these processes in the plane of the camera chip. The article further reports methods to avoid (i) misconceptions due to apparent coloration after transformation of the original signal on the camera chip into color image and (ii) loss of the resolution after reduction of intensity depth from 12-bit to 8-bit.

In this article is reported a construction and some properties of the 5iD viewer, the system recording simultaneously 5 views of a given experimental object. Properties of the system are demonstrated on the analysis of fish schooling behaviour. It is demonstrated the method of instrument calibration which allows inclusion of image distortion and it is proposed and partly tested also the method of distance assessment in the case that only two opposite cameras are available. Finally, we demonstrate how the state trajectory of the behaviour of the fish school may be constructed from the entropy of the system., {"references":["C.W. Reynolds, C.W. (1987). Flocks, herds and schools:Adistributed\nbehavioral model. Computer Graphics, 21(4), 2534.","B. Fine and D. A. Shell. (2013). Unifying Microscopic Flocking Motion\nModels for Virtual, Robotic, and Biological Flock Members. Autonomous\nRobots, 35(23), 195219","A.B. Kao and I.D. Couzin, (2014). Decision accuracy in complex\nenvironments is often maximized by small group sizes. Proceedings of\nthe Royal Society of London Series B 281(1784), 2013305.","http://content.time.com/time/health/article/0,8599,2102612,00.html\n(retrieved August 2014)","J. Werfel, K. Petersen and R. Nagpal (2014). Designing Collective\nBehavior in a Termite-Inspired Robot Construction Team Science, (343),\n754-758","A.I. Dell, J.A. Bender, K. Branson, I.D. Couzin, G.G. de Polavieja,\nL.P.P.J. Noldus, A. Perez-Escudero, P. Perona, A.D. Straw, M.\nWikelski, and U. Brose, (2014) Automated imaging-based tracking and\nits application to ecology. Trends in Ecology and Evolution. 29 (7),\n417-428","http://vision.caltech.edu/bouguetj/calibdoc (retrieved August 2014)","C. Kline, http://www.behaviorworks.com/people/ckline/cornellwww/boid/boids.html\n(retrieved August 2014)","U. Wilensky, (1999). NetLogo. http://ccl.northwestern.edu/netlogo/.\nCenter for Connected Learning and Computer-Based Modeling,\nNorthwestern Institute on Complex Systems, Northwestern University,\nEvanston, IL.\n[10] U. Wilensky, (2005). NetLogo Flocking 3D Alternate model.\nhttp://ccl.northwestern.edu/netlogo/models/Flocking3DAlternate. Center\nfor Connected Learning and Computer-Based Modeling, Northwestern\nInstitute on Complex Systems, Northwestern University, Evanston, IL.\n[11] C. E. Shannon, (1948). \"A Mathematical Theory of Communication\".\nBell System Technical Journal 27 (3), 379423"]}

The amount of data produced by current experiments in systems biology is enormous. Some database and software support for biology experiments exist but usually deal just with some part of data and metadata management. Primary data are only occasionally analyzed in-depth and shared. Studies showed that cost of data sharing is cheaper than experimental work. Experimental costs are several orders higher than data. Therefore, being up to date is a worldwide problem for all users of biology applications. In practice, the problem extends to general fields such as knowledge mining, experiment quality and repeatability, and the philosophical epistemology of biological problems.

Measurement in biological systems became a subject of concern as a consequence of numerous reports on limited reproducibility of experimental results. To reveal origins of this inconsistency, we have examined general features of biological systems as dynamical systems far from not only their chemical equilibrium, but, in most cases, also of their Lyapunov stable states. Thus, in biological experiments, we do not observe states, but distinct trajectories followed by the examined organism. If one of the possible sequences is selected, a minute sub-section of the whole problem is obtained – sometimes in a seemingly highly reproducible manner. But the state of the organism is known only if a complete set of possible trajectories is known. And this is often practically impossible. Therefore, we propose a different framework for reporting and analysis of biological experiments, reflecting the view of non-linear mathematics. This view should be used to avoid overoptimistic results, which have to be consequently retracted or largely complemented. An increase of specification of experimental procedures is the way for better understanding of the scope of paths, which the biological system may be evolving. And it is hidden in the evolution of experimental protocols. Our system bioWes is a tool for objectivization of this knowledge.

This paper presents the whole process of creation of audio-visual speech synthesis system. Such system consists of two main parts, the acoustic synthesis emulating human speech and the facial animation emulating the human lip articulation. The acoustic subsystem is based on concatenation-based speech synthesis. The visual subsystem is designed as a realistic, fully three-dimensional parametrically controllable facial animation model. To be able to parametrically control the animation to emulate human articulation, the set of visual parameters has to be obtained for all basic speech units. To provide realistic animation, the database of lip movements of a real person need to be recorded and expressed by suitable parameterization. The set of control parameters for visual animation is then derived from this database. The 3D model of a head based on a head of a real person also makes the animation more realistic. To obtain such model, a 3D scanning of a real person has to be adopted. We present the design and implementation of above-mentioned process. The aim is to obtain realistic audio-visual speech synthesis with possibility to change the 3D head model according to particular person. The design, acquisition and processing of audio-visual speech corpus for such purpose is presented. Next, the process of both acoustic and visual speech synthesis is described. The visual speech synthesis comprises the tasks of model training, animation control, and co-articulation modelling. A facial animation can also increase intelligibility of a telephone speech to people with hearing disabilities. In such case the textual information to control the animation is not available. Solution to the problem of mapping visual parameters from speech signal either directly or through recognized text is presented. Furthermore, the 3D scanning algorithm is presented. It allows to obtain realistic 3D model based on a head of a real person and thus to personalize the talking head. In the end of this paper, evaluation of intelligibility of the presented audio-visual speech synthesis and its possible applications are presented.

Phase contrast is a noninvasive microscopy imaging technique that is widely used in time-lapse imaging of cells. Resulting images however contain some optical artifacts, which makes automated processing by computer difficult.

We propose a method for characterizing the image—multidimensional projection—of complex, self-organising, system. The method is general and may be used for characterisation of any structured, experimentally observable, complex self-organized systems. The method is based on calculation of information gain by which a point contributes to the total information in the image, the point information gain, PIG. We have also derived related variables, the point information gain entropy PIE and point information gain entropy density PIED. The later values are unique to a structured information and may be used for analysis of similarity by clustering, identification of states etc. We illustrate our key results using the example of living cell. We discuss practical limits of the analogy between this observable self-organising system and its possible theoretical model using an example of chaotic attractor.

Part 2: Full Papers; International audience; We propose a method for characterizing structured, experimentally observable, complex self-organized systems. The method in question is based on the observation that number of self-organized systems can be mathematically perceived as consisting of several interconnected multifractal components. We illustrate our key results with ensuing applications. The relation of the results obtained to known examples of strange attractors is also discussed.

Our analysis is based on the assumption that the metabolic and signal pathways substantiate non-linear dynamic processes which are responsible for asymptotic stability of biological systems. Observed events, not pathways themselves, are the elementary asymptotically stable objects to be studied. This assumption is theoretically supported by observed structures in a relatively simple pseudo-chemical agentbased model. The state space is given by coefficients of Renyi information entropy. Each combination of Renyi coefficients gives us one subtraction of the whole trajectory. The single cell trajectory should be divided into several clusters, once the trajectory is constructed. Each cluster of the trajectory represents an event or subset of the states of the cell. Size and position of clusters depends on the trajectory and on number of clusters. We propose a recipe, using the rules of the generalized stochastic system theory, how to extract individual trajectories of the multifractal system - the biological stochastic attractor. This set of trajectories is then utilized for thermodynamic representation of the biological chaotic attractor. Our analysis is strictly based on experiment with all its practical limits. We present implementation of analysis of development of cell monolayer observed by microphotography

We report objective analysis of information in the microscopic image of the cell monolayer. The process of transfer of information about the cell by the microscope is analyzed in terms of the classical Shannon information transfer scheme. The information source is the biological object, the information transfer channel is the whole microscope including the camera chip. The destination is the model of biological system. The information contribution is analyzed as information carried by a point to overall information in the image. Subsequently we obtain information reflection of the biological object. This is transformed in the biological model which, in information terminology, is the destination. This, we propose, should be constructed as state transitions in individual cells modulated by information bonds between the cells. We show examples of detected cell states in multidimensional state space. This space is reflected as colour channel intensity phenomenological state space. We have also observed information bonds and show examples of them.

The construction of state trajectory of the cell is not a simple task. It must be decided what are the state variables. Since we work with coloured images, it sounds logical to start with the trajectory in RGB colour space. Each axis is then processed via several Renyi entropies. The value of Renyi coefficient spread or collapsed the trajectory along the axis of the state space. Each combination of Renyi coefficients gives us one subtraction of the whole trajectory. The major issue is how to choose the proper combination. However, all subtractions are correct. The single cell trajectory should be divided into several clusters, once the trajectory is constructed. Each cluster of the trajectory represents an event or subset of the states of the cell. Size and position of clusters depends on the trajectory and on number of clusters. We proposed eight clusters now as a first estimation, satisfied by the results: Clusters are well separated; images in transitions between clusters show some changes. Changes are also observable in images at the borders of the clusters. If we compare content of the clusters in different trajectories some images stay in the same cluster but some images may change the cluster. This is caused by the method of acquisition of the trajectory. The different coefficient in the Renyi equation highlights different part of the image so the trajectory can be little bit different as well as size, position and content of clusters.

In this paper, we present a solution to the problem of tracking 3D information about the shape of lips from 2D picture of a speaker. We focus on lip-tracking of audio-visual speech recordings from the Czech in-vehicle audio-visual speech corpus (CIVAVC). The corpus consists of 4 h 40 min records of audiovisual speech of driver recorded in a car during driving in an usual traffic. In real conditions a head of a speaker (a car driver) can move and turn in various directions. To cope with these movements and to avoid recognition errors caused by changing 3D position of lips, our algorithm utilizes a 3D-model-based approach to the lip-tracking process. First, we present a method for creating and clustering the lip shape models. We derived 20 basic 3D models of the lip shape from real utterances of the speaker for representation of all lip movements. Next, we describe an algorithm for finding the shape of the lips in a picture using image processing. Further we present application of a distance function for choosing the best model for representation of the lip shape obtained by image processing. Finally we depict the results of the lip-tracking and its using for lip-reading.

International audience; The main aim of this study was to develop a new objective method for evaluating the impacts of different diets on the live fish skin using image-based features. In total, one-hundred and sixty rainbow trout (Oncorhynchus mykiss) were fed either a fish-meal based diet (80 fish) or a 100% plant-based diet (80 fish) and photographed using consumer-grade digital camera. Twenty-three colour features and four texture features were extracted. Four different classification methods were used to evaluate fish diets including Random forest (RF), Support vector machine (SVM), Logistic regression (LR) and k-Nearest neighbours (k-NN). The SVM with radial based kernel provided the best classifier with correct classification rate (CCR) of 82% and Kappa coefficient of 0.65. Although the both LR and RF methods were less accurate than SVM, they achieved good classification with CCR 75% and 70% respectively. The k-NN was the least accurate (40%) classification model. Overall, it can be concluded that consumer-grade digital cameras could be employed as the fast, accurate and non-invasive sensor for classifying rainbow trout based on their diets. Furthermore, these was a close association between image-based features and fish diet received during cultivation. These procedures can be used as non-invasive, accurate and precise approaches for monitoring fish status during the cultivation by evaluating diet's effects on fish skin.