A framework for automatic feature extraction from airborne light detection and ranging data

Recent advances in airborne Light Detection and Ranging (LIDAR) technology allow rapid and inexpensive measurements of topography over large areas. Airborne LIDAR systems usually return a 3-dimensional cloud of point measurements from reflective objects scanned by the laser beneath the flight path. This technology is becoming a primary method for extracting information of different kinds of geometrical objects, such as high-resolution digital terrain models (DTMs), buildings and trees, etc. In the past decade, LIDAR gets more and more interest from researchers in the field of remote sensing and GIS. Compared to the traditional data sources, such as aerial photography and satellite images, LIDAR measurements are not influenced by sun shadow and relief displacement. However, voluminous data pose a new challenge for automated extraction the geometrical information from LIDAR measurements because many raster image processing techniques cannot be directly applied to irregularly spaced LIDAR points. ^ In this dissertation, a framework is proposed to filter out information about different kinds of geometrical objects, such as terrain and buildings from LIDAR automatically. They are essential to numerous applications such as flood modeling, landslide prediction and hurricane animation. The framework consists of several intuitive algorithms. Firstly, a progressive morphological filter was developed to detect non-ground LIDAR measurements. By gradually increasing the window size and elevation difference threshold of the filter, the measurements of vehicles, vegetation, and buildings are removed, while ground data are preserved. Then, building measurements are identified from no-ground measurements using a region growing algorithm based on the plane-fitting technique. Raw footprints for segmented building measurements are derived by connecting boundary points and are further simplified and adjusted by several proposed operations to remove noise, which is caused by irregularly spaced LIDAR measurements. To reconstruct 3D building models, the raw 2D topology of each building is first extracted and then further adjusted. Since the adjusting operations for simple building models do not work well on 2D topology, 2D snake algorithm is proposed to adjust 2D topology. The 2D snake algorithm consists of newly defined energy functions for topology adjusting and a linear algorithm to find the minimal energy value of 2D snake problems. Data sets from urbanized areas including large institutional, commercial, and small residential buildings were employed to test the proposed framework. The results demonstrated that the proposed framework achieves a very good performance. ^

Development of a surface-enhanced raman spectroscopy method for the detection of benzodiazepines in urine

Benzodiazepines are among the most prescribed compounds for anti-anxiety and are present in many toxicological screens. These drugs are also prominent in the commission of drug facilitated sexual assaults due their effects on the central nervous system. Due to their potency, a low dose of these compounds is often administered to victims; therefore, the target detection limit for these compounds in biological samples is 10 ng/mL. Currently these compounds are predominantly analyzed using immunoassay techniques; however more specific screening methods are needed. ^ The goal of this dissertation was to develop a rapid, specific screening technique for benzodiazepines in urine samples utilizing surface-enhanced Raman spectroscopy (SERS), which has previously been shown be capable of to detect trace quantities of pharmaceutical compounds in aqueous solutions. Surface enhanced Raman spectroscopy has the advantage of overcoming the low sensitivity and fluorescence effects seen with conventional Raman spectroscopy. The spectra are obtained by applying an analyte onto a SERS-active metal substrate such as colloidal metal particles. SERS signals can be further increased with the addition of aggregate solutions. These agents cause the nanoparticles to amass and form hot-spots which increase the signal intensity. ^ In this work, the colloidal particles are spherical gold nanoparticles in aqueous solution with an average size of approximately 30 nm. The optimum aggregating agent for the detection of benzodiazepines was determined to be 16.7 mM MgCl2, providing the highest signal intensities at the lowest drug concentrations with limits of detection between 0.5 and 127 ng/mL. A supported liquid extraction technique was utilized as a rapid clean extraction for benzodiazepines from urine at a pH of 5.0, allowing for clean extraction with limits of detection between 6 and 640 ng/mL. It was shown that at this pH other drugs that are prevalent in urine samples can be removed providing the selective detection of the benzodiazepine of interest. ^ This technique has been shown to provide rapid (less than twenty minutes), sensitive, and specific detection of benzodiazepines at low concentrations in urine. It provides the forensic community with a sensitive and specific screening technique for the detection of benzodiazepines in drug facilitated assault cases.^

Development of a Surface-Enhanced Raman Spectroscopy Method for the Detection of Benzodiazepines in Urine

Benzodiazepines are among the most prescribed compounds for anti-anxiety and are present in many toxicological screens. These drugs are also prominent in the commission of drug facilitated sexual assaults due their effects on the central nervous system. Due to their potency, a low dose of these compounds is often administered to victims; therefore, the target detection limit for these compounds in biological samples is 10 ng/mL. Currently these compounds are predominantly analyzed using immunoassay techniques; however more specific screening methods are needed. The goal of this dissertation was to develop a rapid, specific screening technique for benzodiazepines in urine samples utilizing surface-enhanced Raman spectroscopy (SERS), which has previously been shown be capable of to detect trace quantities of pharmaceutical compounds in aqueous solutions. Surface enhanced Raman spectroscopy has the advantage of overcoming the low sensitivity and fluorescence effects seen with conventional Raman spectroscopy. The spectra are obtained by applying an analyte onto a SERS-active metal substrate such as colloidal metal particles. SERS signals can be further increased with the addition of aggregate solutions. These agents cause the nanoparticles to amass and form hot-spots which increase the signal intensity. In this work, the colloidal particles are spherical gold nanoparticles in aqueous solution with an average size of approximately 30 nm. The optimum aggregating agent for the detection of benzodiazepines was determined to be 16.7 mM MgCl2, providing the highest signal intensities at the lowest drug concentrations with limits of detection between 0.5 and 127 ng/mL. A supported liquid extraction technique was utilized as a rapid clean extraction for benzodiazepines from urine at a pH of 5.0, allowing for clean extraction with limits of detection between 6 and 640 ng/mL. It was shown that at this pH other drugs that are prevalent in urine samples can be removed providing the selective detection of the benzodiazepine of interest. This technique has been shown to provide rapid (less than twenty minutes), sensitive, and specific detection of benzodiazepines at low concentrations in urine. It provides the forensic community with a sensitive and specific screening technique for the detection of benzodiazepines in drug facilitated assault cases.

The neurotoxin β-N-methylamino-L-alanine (BMAA) : Sources, bioaccumulation and extraction procedures

β-methylamino-L-alanine (BMAA) is a neurotoxin linked to neurodegeneration, which is manifested in the devastating human diseases amyotrophic lateral sclerosis, Alzheimer’s and Parkinson’s disease. This neurotoxin is known to be produced by almost all tested species within the cyanobacterial phylum including free living as well as the symbiotic strains. The global distribution of the BMAA producers ranges from a terrestrial ecosystem on the Island of Guam in the Pacific Ocean to an aquatic ecosystem in Northern Europe, the Baltic Sea, where annually massive surface blooms occur. BMAA had been shown to accumulate in the Baltic Sea food web, with highest levels in the bottom dwelling fish-species as well as in mollusks. One of the aims of this thesis was to test the bottom-dwelling bioaccumulation hypothesis by using a larger number of samples allowing a statistical evaluation. Hence, a large set of fish individuals from the lake Finjasjön, were caught and the BMAA concentrations in different tissues were related to the season of catching, fish gender, total weight and species. The results reveal that fish total weight and fish species were positively correlated with BMAA concentration in the fish brain. Therefore, significantly higher concentrations of BMAA in the brain were detected in plankti-benthivorous fish species and heavier (potentially older) individuals. Another goal was to investigate the potential production of BMAA by other phytoplankton organisms. Therefore, diatom cultures were investigated and confirmed to produce BMAA, even in higher concentrations than cyanobacteria. All diatom cultures studied during this thesis work were show to contain BMAA, as well as one dinoflagellate species. This might imply that the environmental spread of BMAA in aquatic ecosystems is even higher than previously thought. Earlier reports on the concentration of BMAA in different organisms have shown highly variable results and the methods used for quantification have been intensively discussed in the scientific community. In the most recent studies, liquid chromatography-tandem mass spectrometry (LC-MS/MS) has become the instrument of choice, due to its high sensitivity and selectivity. Even so, different studies show quite variable concentrations of BMAA. In this thesis, three of the most common BMAA extraction protocols were evaluated in order to find out if the extraction could be one of the sources of variability. It was found that the method involving precipitation of proteins using trichloroacetic acid gave the best performance, complying with all in-house validation criteria. However, extractions of diatom and cyanobacteria cultures with this validated method and quantified using LC-MS/MS still resulted in variable BMAA concentrations, which suggest that also biological reasons contribute to the discrepancies. The current knowledge on the environmental factors that can induce or reduce BMAA production is still limited. In cyanobacteria, production of BMAA was earlier shown to be negative correlated with nitrogen availability – both in laboratory cultures as well as in natural populations. Based on this observation, it was suggested that in unicellular non-diazotrophic cyanobacteria, BMAA might take part in nitrogen metabolism. In order to find out if BMAA has a similar role in diatoms, BMAA was added to two diatom species in culture, in concentrations corresponding to those earlier found in the diatoms. The results suggest that BMAA might induce a nitrogen starvation signal in diatoms, as was earlier observed in cyanobacteria. However, diatoms recover shortly by the extracellular presence of excreted ammonia. Thus, also in diatoms, BMAA might be involved in the nitrogen balance in the cell.

Extraction system and determination of PAH in seawater and it implementation in submarine vehicles

[EN]Policyclyc aromatic hydrocarbons (PAHs) are a potential risk for human health and marine biota in general that make necessary the monitorization of them. A miniaturized extraction system capable to extract PAHs from seawater was developed and optimized with the objective of implement it in an oceanographic buoy in the future. An analytical method was optimized by high performance liquid chromatography for the determination of extracted PAHs by the extraction system. The analytical method was validated and applicated to real samples of differents points of Gran Canaria. The method has enough sensitivity to detect and quantify concentrations below the concentrations established in the legislation. In some places where samples were taken some compounds exceed the legislation while other compounds follow it

FPGA-based architecture for hyperspectral endmember extraction

Hyperspectral instruments have been incorporated in satellite missions, providing data of high spectral resolution of the Earth. This data can be used in remote sensing applications, such as, target detection, hazard prevention, and monitoring oil spills, among others. In most of these applications, one of the requirements of paramount importance is the ability to give real-time or near real-time response. Recently, onboard processing systems have emerged, in order to overcome the huge amount of data to transfer from the satellite to the ground station, and thus, avoiding delays between hyperspectral image acquisition and its interpretation. For this purpose, compact reconfigurable hardware modules, such as field programmable gate arrays (FPGAs) are widely used. This paper proposes a parallel FPGA-based architecture for endmember’s signature extraction. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data sets collected by the NASA’s Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the Cuprite mining district in Nevada. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems, opening new perspectives for onboard hyperspectral image processing.

Use of time-resolved spectroscopy as a method to monitor carotenoids present in tomato extract obtained using ultrasound treatment

Introduction Compounds exhibiting antioxidant activity have received much interest in the food industry because of their potential health benefits. Carotenoids such as lycopene, which in the human diet mainly derives from tomatoes (Solanum lycopersicum), have attracted much attention in this aspect and the study of their extraction, processing and storage procedures is of importance. Optical techniques potentially offer advantageous non-invasive and specific methods to monitor them. Objectives To obtain both fluorescence and Raman information to ascertain if ultrasound assisted extraction from tomato pulp has a detrimental effect on lycopene. Method Use of time-resolved fluorescence spectroscopy to monitor carotenoids in a hexane extract obtained from tomato pulp with application of ultrasound treatment (583 kHz). The resultant spectra were a combination of scattering and fluorescence. Because of their different timescales, decay associated spectra could be used to separate fluorescence and Raman information. This simultaneous acquisition of two complementary techniques was coupled with a very high time-resolution fluorescence lifetime measurement of the lycopene. Results Spectroscopic data showed the presence of phytofluene and chlorophyll in addition to lycopene in the tomato extract. The time-resolved spectral measurement containing both fluorescence and Raman data, coupled with high resolution time-resolved measurements, where a lifetime of ~5 ps was attributed to lycopene, indicated lycopene appeared unaltered by ultrasound treatment. Detrimental changes were, however, observed in both chlorophyll and phytofluene contributions. Conclusion Extracted lycopene appeared unaffected by ultrasound treatment, while other constituents (chlorophyll and phytofluene) were degraded.

Automatic Glaucoma Detection Based on Optic Disc Segmentation and Texture Feature Extraction

The use of digital image processing techniques is prominent in medical settings for the automatic diagnosis of diseases. Glaucoma is the second leading cause of blindness in the world and it has no cure. Currently, there are treatments to prevent vision loss, but the disease must be detected in the early stages. Thus, the objective of this work is to develop an automatic detection method of Glaucoma in retinal images. The methodology used in the study were: acquisition of image database, Optic Disc segmentation, texture feature extraction in different color models and classification of images in glaucomatous or not. We obtained results of 93% accuracy

Engraulis encrasicolus (Linnaeus, 1758): technical report about extraction and recognition of the digestive tract contents in early stages of the life cycle

The study of ichthyio-plankton stages and its relations with the environment and other organisms is therefore crucial for a correct use of fishery resources. In this context, the extraction and the analysis of the content of the digestive tract, is a key method for the identification of the diet in early larval stages, the determination of the resources they rely on and possibly a comparison with the diet of other species. Additionally this approach could be useful in determination on occurrence of species competition. This technique is preceded by the analysis of morphometric data (Blackith & Reyment, 1971; Marcus, 1990), that is the acquisition of quantitative variables measured from the morphology of the object of study. They are linear distances, count, angles and ratios. The subsequent application of multivariate statistical methods, aims to quantify the changes in morphological measures between and within groups, relating them to the type and size of prey and evaluate if some changes appear in food choices along the larvae growth.

Analysis of N-nitrosames in water using micellar electrokinetic chromatography (MEKC) and development of online and offline methods of extraction and enrichment of neutral polar analytes

Evaluation of the quality of the environment is essential for human wellness as pollutants in trace amounts can cause serious health problem. Nitrosamines are a group of compounds that are considered potential carcinogens and can be found in drinking water (as disinfection byproducts), foods, beverages and cosmetics. To monitor the level of these compounds to minimize daily intakes, fast and reliable analytical techniques are required. As these compounds are relatively highly polar, extraction and enrichment from environmental samples (aqueous) are challenging. Also, the trend of analytical techniques toward the reduction of sample size and minimization of organic solvent use demands new methods of analysis. In light of fulfilling these requirements, a new method of online preconcentration tailored to an electrokinetic chromatography is introduced. In this method, electroosmotic flow (EOF) was suppressed to increase the interaction time between analyte and micellar phase, therefore the only force to mobilize the neutral analytes is the interaction of analyte with moving micelles. In absence of EOF, polarity of applied potential was switched (negative or positive) to force (anionic or cationic) micelles to move toward the detector. To avoid the excessive band broadening due to longer analysis time caused by slow moving micelles, auxiliary pressure was introduced to boost the micelle movement toward the detector using an in house designed and built apparatus. Applying the external auxiliary pressure significantly reduced the analysis times without compromising separation efficiency. Parameters, such as type of surfactants, composition of background electrolyte (BGE), type of capillary, matrix effect, organic modifiers, etc., were evaluated in optimization of the method. The enrichment factors for targeted analytes were impressive, particularly; cationic surfactants were shown to be suitable for analysis of nitrosamines due to their ability to act as hydrogen bond donors. Ammonium perfluorooctanoate (APFO) also showed remarkable results in term of peak shapes and number of theoretical plates. It was shown that the separation results were best when a high conductivity sample was paired with a BGE of lower conductivity. Using higher surfactant concentrations (up to 200 mM SDS) than usual (50 mM SDS) for micellar electrokinetic chromatography (MEKC) improved the sweeping. A new method for micro-extraction and enrichment of highly polar neutral analytes (N-Nitrosamines in particular) based on three-phase drop micro-extraction was introduced and its performance studied. In this method, a new device using some easy-to-find components was fabricated and its operation and application demonstrated. Compared to conventional extraction methods (liquid-liquid extraction), consumption of organic solvents and operation times were significantly lower.

Automatic dynamic mask extraction for PIV images containing an unsteady interface, bubbles, and a moving structure

When performing Particle Image Velocimetry (PIV) measurements in complex fluid flows with moving interfaces and a two-phase flow, it is necessary to develop a mask to remove non-physical measurements. This is the case when studying, for example, the complex bubble sweep-down phenomenon observed in oceanographic research vessels. Indeed, in such a configuration, the presence of an unsteady free surface, of a solid–liquid interface and of bubbles in the PIV frame, leads to generate numerous laser reflections and therefore spurious velocity vectors. In this note, an image masking process is developed to successively identify the boundaries of the ship and the free surface interface. As the presence of the solid hull surface induces laser reflections, the hull edge contours are simply detected in the first PIV frame and dynamically estimated for consecutive ones. As for the unsteady surface determination, a specific process is implemented like the following: i) the edge detection of the gradient magnitude in the PIV frame, ii) the extraction of the particles by filtering high-intensity large areas related to the bubbles and/or hull reflections, iii) the extraction of the rough region containing these particles and their reflections, iv) the removal of these reflections. The unsteady surface is finally obtained with a fifth-order polynomial interpolation. The resulted free surface is successfully validated from the Fourier analysis and by visualizing selected PIV images containing numerous spurious high intensity areas. This paper demonstrates how this data analysis process leads to PIV images database without reflections and an automatic detection of both the free surface and the rigid body. An application of this new mask is finally detailed, allowing a preliminary analysis of the hydrodynamic flow.

Extraction and purification of immunoglobulin G with aqueous biphasic systems

The immune system is able to produce antibodies, which have the capacity to recognize and to bind to foreign molecules or pathogenic organisms. Currently, there are a diversity of diseases that can be treated with antibodies, like immunoglobulins G (IgG). Thereby, the development of cost-efficient processes for their extraction and purification is an area of main interest in biotechnology. Aqueous biphasic systems (ABS) have been investigated for this purpose, once they allow the reduction of costs and the number of steps involved in the process, when compared with conventional methods. Nevertheless, typical ABS have not showed to be selective, resulting in low purification factors and yields. In this context, the addition of ionic liquids (ILs) as adjuvants can be a viable and potential alternative to tailor the selectivity of these systems. In this work, ABS composed of polyethylene glycol (PEG) of different molecular weight, and a biodegradable salt (potassium citrate) using ILs as adjuvants (5 wt%), were studied for the extraction and purification of IgG from a rabbit source. Initially, it was tested the extraction time, the effect on the molecular weight of PEG in a buffer solution of K3C6H5O7/C6H8O7 at pH≈7, and the effect of pH (59) on the yield (YIgG) and extraction efficiency (EEIgG%) of IgG. The best results regarding EEIgG% were achieved with a centrifugation step at 1000 rpm, during 10 min, in order to promote the separation of phases followed by 120 min of equilibrium. This procedure was then applied to the remaining experiments. The results obtained in the study of PEGs with different molecular weights, revealed a high affinity of IgG for the PEG-rich phase, and particularly for PEGs of lower molecular weight (EEIgG% of 96 % with PEG 400). On the other hand, the variation of pH in the buffer solution did not show a significant effect on the EEIgG%. Finally, it was evaluated the influence of the addition of different ILs (5% wt) on the IgG extraction in ABS composed of PEG 400 at pH≈7. In these studies, it was possible to obtain EEIgG% of 100% with the ILs composed of the anions [TOS]-, [CH3CO2]-and Cl-, although the obtained YIgG% were lower than 40%. On the other hand, the ILs composed of the anions Br-, as well as of the cation [C10mim]+, although not leading to EEIgG% of 100%, provide an increase in the YIgG%. ABS composed of PEG, a biodegradable organic salt and ILs as adjuvants, revealed to be an alternative and promising method to purify IgG. However, additional studies are still required in order to reduce the loss of IgG.

Study of salinity gradients in the Persian Gulf and an experimental model for electric energy extraction from them using nano-membranes

Salinity gradient power (SGP) is the energy that can be obtained from the mixing entropy of two solutions with a different salt concentration. River estuary, as a place for mixing salt water and fresh water, has a huge potential of this renewable energy. In this study, this potential in the estuaries of rivers leading to the Persian Gulf and the factors affecting it are analysis and assessment. Since most of the full water rivers are in the Asia, this continent with the potential power of 338GW is a second major source of energy from the salinity gradient power in the world (Wetsus institute, 2009). Persian Gulf, with the proper salinity gradient in its river estuaries, has Particular importance for extraction of this energy. Considering the total river flow into the Persian Gulf, which is approximately equal to 3486 m3/s, the amount of theoretical extractable power from salinity gradient in this region is 5.2GW. Iran, with its numerous rivers along the coast of the Persian Gulf, has a great share of this energy source. For example, with study calculations done on data from three hydrometery stations located on the Arvand River, Khorramshahr Station with releasing 1.91M/ energy which is obtained by combining 1.26m3 river water with 0.74 m3 sea water, is devoted to itself extracting the maximum amount of extractable energy. Considering the average of annual discharge of Arvand River in Khorramshahr hydrometery station, the amount of theoretical extractable power is 955 MW. Another part of parameters that are studied in this research, are the intrusion length of salt water and its flushing time in the estuary that have a significant influence on the salinity gradient power. According to the calculation done in conditions HWS and the average discharge of rivers, the maximum of salinity intrusion length in to the estuary of the river by 41km is related to Arvand River and the lowest with 8km is for Helle River. Also the highest rate of salt water flushing time in the estuary with 9.8 days is related to the Arvand River and the lowest with 3.3 days is for Helle River. Influence of these two parameters on reduces the amount of extractable energy from salinity gradient power as well as can be seen in the estuaries of the rivers studied. For example, at the estuary of the Arvand River in the interval 8.9 days, salinity gradient power decreases 9.2%. But another part of this research focuses on the design of a suitable system for extracting electrical energy from the salinity gradient. So far, five methods have been proposed to convert this energy to electricity that among them, reverse electro-dialysis (RED) method and pressure-retarded osmosis (PRO) method have special importance in practical terms. In theory both techniques generate the same amount of energy from given volumes of sea and river water with specified salinity; in practice the RED technique seems to be more attractive for power generation using sea water and river water. Because it is less necessity of salinity gradient to PRO method. In addition to this, in RED method, it does not need to use turbine to change energy and the electricity generation is started when two solutions are mixed. In this research, the power density and the efficiency of generated energy was assessment by designing a physical method. The physical designed model is an unicellular reverse electro-dialysis battery with nano heterogenic membrane has 20cmx20cm dimension, which produced power density 0.58 W/m2 by using river water (1 g NaCl/lit) and sea water (30 g NaCl/lit) in laboratorial condition. This value was obtained because of nano method used on the membrane of this system and suitable design of the cell which led to increase the yield of the system efficiency 11% more than non nano ones.

Extraction and detection of mycotoxins in medicinal and aromatic plants: a case study with Aloysia citrodora P.

Plants frequently suffer contaminations by toxigenic fungi, and their mycotoxins can be produced throughout growth, harvest, drying and storage periods. The objective of this work was to validate a method for detection of toxins in medicinal and aromatic plants, through a fast and highly sensitive method, optimizing the joint co-extraction of aflatoxins (AF: AFB1, AFB2, AFG1 and AFG2) and ochratoxin A (OTA) by using Aloysia citrodora P. (lemon verbena) as a case study. For optimization purposes, samples were spiked (n=3) with standard solutions of a mix of the four AFs and OTA at 10 ng/g for AFB1, AFG1 and OTA, and at 6 ng/g of AFB2 and AFG2. Several extraction procedures were tested: i) ultrasound-assisted extraction in sodium chloride and methanol/water (80:20, v/v) [(OTA+AFs)1]; ii) maceration in methanol/1% NaHCO3 (70:30, v/v) [(OTA+AFs)2]; iii) maceration in methanol/1% NaHCO3 (70:30, v/v) (OTA1); and iv) maceration in sodium chloride and methanol/water (80:20, v/v) (AF1). AF and OTA were purified using the mycotoxin-specific immunoaffinity columns AflaTest WB and OchraTest WB (VICAM), respectively. Separation was performed with a Merck Chromolith Performance C18 column (100 x 4.6 mm) by reverse-phase HPLC coupled to a fluorescence detector (FLD) and a photochemical derivatization system (for AF). The recoveries obtained from the spiked samples showed that the single-extraction methods (OTA1 and AF1) performed better than co-extraction methods. For in-house validation of the selected methods OTA1 and AF1, recovery and precision were determined (n=6). The recovery of OTA for method OTA1 was 81%, and intermediate precision (RSDint) was 1.1%. The recoveries of AFB1, AFB2, AFG1 and AFG2 ranged from 64% to 110% for method AF1, with RSDint lower than 5%. Methods OTA1 and AF1 showed precision and recoveries within the legislated values and were found to be suitable for the extraction of OTA and AF for the matrix under study.

Active Foreground Region Extraction and Tracking for Sports Video Annotation

Automatic video segmentation plays a vital role in sports videos annotation. This paper presents a fully automatic and computationally efficient algorithm for analysis of sports videos. Various methods of automatic shot boundary detection have been proposed to perform automatic video segmentation. These investigations mainly concentrate on detecting fades and dissolves for fast processing of the entire video scene without providing any additional feedback on object relativity within the shots. The goal of the proposed method is to identify regions that perform certain activities in a scene. The model uses some low-level feature video processing algorithms to extract the shot boundaries from a video scene and to identify dominant colours within these boundaries. An object classification method is used for clustering the seed distributions of the dominant colours to homogeneous regions. Using a simple tracking method a classification of these regions to active or static is performed. The efficiency of the proposed framework is demonstrated over a standard video benchmark with numerous types of sport events and the experimental results show that our algorithm can be used with high accuracy for automatic annotation of active regions for sport videos.