Using Digital Video Analysis to Monitor Driver Behavior at Intersections

Commercially available instruments for road-side data collection take highly limited measurements, require extensive manual input, or are too expensive for widespread use. However, inexpensive computer vision techniques for digital video analysis can be applied to automate the monitoring of driver, vehicle, and pedestrian behaviors. These techniques can measure safety-related variables that cannot be easily measured using existing sensors. The use of these techniques will lead to an improved understanding of the decisions made by drivers at intersections. These automated techniques allow the collection of large amounts of safety-related data in a relatively short amount of time. There is a need to develop an easily deployable system to utilize these new techniques. This project implemented and tested a digital video analysis system for use at intersections. A prototype video recording system was developed for field deployment. A computer interface was implemented and served to simplify and automate the data analysis and the data review process. Driver behavior was measured at urban and rural non-signalized intersections. Recorded digital video was analyzed and used to test the system.

Image Analysis for the Characterization of Materials for Highway Construction : Phase I, Progress Report, HR-346, 1992

The major objective of this project is to evaluate image analysis for characterizing air voids in Portland cement contract (PCC) and asphalt concrete (AC) and aggregate gradation in asphalt concrete. Phase 1 of this project has concentrated on evaluation and refinement of sample preparation techniques, evaluation of methods and instruments for conducting image analysis, and finally, analysis and comparison of a select portion of samples. Preliminary results suggest a strong correlation between the results obtained from the linear traverse method and image analysis methods for determining percent air voids in concrete. Preliminary work with asphalt samples has shown that damage caused by a high vacuum of the conventional scanning electron microscope (SEM) may too disruptive. Alternative solutions have been explored, including confocal microscopy and low vacuum electron microscopy. Additionally, a conventional high vacuum SEM operating at a marginal operating vacuum may suffice.

Retinal Image Analysis Using Machine Vision

The topic of this thesis is studying how lesions in retina caused by diabetic retinopathy can be detected from color fundus images by using machine vision methods. Methods for equalizing uneven illumination in fundus images, detecting regions of poor image quality due toinadequate illumination, and recognizing abnormal lesions were developed duringthe work. The developed methods exploit mainly the color information and simpleshape features to detect lesions. In addition, a graphical tool for collecting lesion data was developed. The tool was used by an ophthalmologist who marked lesions in the images to help method development and evaluation. The tool is a general purpose one, and thus it is possible to reuse the tool in similar projects.The developed methods were tested with a separate test set of 128 color fundus images. From test results it was calculated how accurately methods classify abnormal funduses as abnormal (sensitivity) and healthy funduses as normal (specificity). The sensitivity values were 92% for hemorrhages, 73% for red small dots (microaneurysms and small hemorrhages), and 77% for exudates (hard and soft exudates). The specificity values were 75% for hemorrhages, 70% for red small dots, and 50% for exudates. Thus, the developed methods detected hemorrhages accurately and microaneurysms and exudates moderately.

Environmental Monitoring using Image Analysis

Tärkeä tehtävä ympäristön tarkkailussa on arvioida ympäristön nykyinen tila ja ihmisen siihen aiheuttamat muutokset sekä analysoida ja etsiä näiden yhtenäiset suhteet. Ympäristön muuttumista voidaan hallita keräämällä ja analysoimalla tietoa. Tässä diplomityössä on tutkittu vesikasvillisuudessa hai vainuja muutoksia käyttäen etäältä hankittua mittausdataa ja kuvan analysointimenetelmiä. Ympäristön tarkkailuun on käytetty Suomen suurimmasta järvestä Saimaasta vuosina 1996 ja 1999 otettuja ilmakuvia. Ensimmäinen kuva-analyysin vaihe on geometrinen korjaus, jonka tarkoituksena on kohdistaa ja suhteuttaa otetut kuvat samaan koordinaattijärjestelmään. Toinen vaihe on kohdistaa vastaavat paikalliset alueet ja tunnistaa kasvillisuuden muuttuminen. Kasvillisuuden tunnistamiseen on käytetty erilaisia lähestymistapoja sisältäen valvottuja ja valvomattomia tunnistustapoja. Tutkimuksessa käytettiin aitoa, kohinoista mittausdataa, minkä perusteella tehdyt kokeet antoivat hyviä tuloksia tutkimuksen onnistumisesta.

Particle shape and orientation in laser diffraction and static image analysis size distribution analysis of micrometer sized rectangular particles

Laser diffraction (LD) and static image analysis (SIA) of rectangular particles [United States Pharmacopeia, USP30-NF25, General Chapter <776>, Optical Miroscopy.] have been systematically studied. To rule out sample dispersion and particle orientation as the root cause of differences in size distribution profiles, we immobilize powder samples on a glass plate by means of a dry disperser. For a defined region of the glass plate, we measure the diffraction pattern as induced by the dispersed particles, and the 2D dimensions of the individual particles using LD and optical microscopy, respectively. We demonstrate a correlation between LD and SIA, with the scattering intensity of the individual particles as the dominant factor. In theory, the scattering intensity is related to the square of the projected area of both spherical and rectangular particles. In traditional LD the size distribution profile is dominated by the maximum projected area of the particles (A). The diffraction diameters of a rectangular particle with length L and breadth B as measured by the LD instrument approximately correspond to spheres of diameter ØL and ØB respectively. Differences in the scattering intensity between spherical and rectangular particles suggest that the contribution made to the overall LD volume probability distribution by each rectangular particle is proportional to A2/L and A2/B. Accordingly, for rectangular particles the scattering intensity weighted diffraction diameter (SIWDD) explains an overestimation of their shortest dimension and an underestimation of their longest dimension. This study analyzes various samples of particles whose length ranges from approximately 10 to 1000 μm. The correlation we demonstrate between LD and SIA can be used to improve validation of LD methods based on SIA data for a variety of pharmaceutical powders all with a different rectangular particle size and shape.

Analysis of resuspension and sedimentation processes of unaltered fish faeces using image analysis

Postprint (published version)

Characterisation of pigment particles by scanning electron microscope and image analysis programs

Coating and filler pigments have strong influence to the properties of the paper. Filler content can be even over 30 % and pigment content in coating is about 85-95 weight percent. The physical and chemical properties of the pigments are different and the knowledge of these properties is important for optimising of optical and printing properties of the paper. The size and shape of pigment particles can be measured by different analysers which can be based on sedimentation, laser diffraction, changes in electric field etc. In this master's thesis was researched particle properties especially by scanning electron microscope (SEM) and image analysis programs. Research included nine pigments with different particle size and shape. Pigments were analysed by two image analysis programs (INCA Feature and Poikki), Coulter LS230 (laser diffraction) and SediGraph 5100 (sedimentation). The results were compared to perceive the effect of particle shape to the performance of the analysers. Only image analysis programs gave parameters of the particle shape. One part of research was also the sample preparation for SEM. Individual particles should be separated and distinct in ideal sample. Analysing methods gave different results but results from image analysis programs corresponded even to sedimentation or to laser diffraction depending on the particle shape. Detailed analysis of the particle shape required high magnification in SEM, but measured parameters described very well the shape of the particles. Large particles (ecd~1 µm) could be used also in 3D-modelling which enabled the measurement of the thickness of the particles. Scanning electron microscope and image analysis programs were effective and multifunctional tools for particle analyses. Development and experience will devise the usability of analysing method in routine use.

Computational Techniques for Spectral Image Analysis

Multispectral images are becoming more common in the field of remote sensing, computer vision, and industrial applications. Due to the high accuracy of the multispectral information, it can be used as an important quality factor in the inspection of industrial products. Recently, the development on multispectral imaging systems and the computational analysis on the multispectral images have been the focus of a growing interest. In this thesis, three areas of multispectral image analysis are considered. First, a method for analyzing multispectral textured images was developed. The method is based on a spectral cooccurrence matrix, which contains information of the joint distribution of spectral classes in a spectral domain. Next, a procedure for estimating the illumination spectrum of the color images was developed. Proposed method can be used, for example, in color constancy, color correction, and in the content based search from color image databases. Finally, color filters for the optical pattern recognition were designed, and a prototype of a spectral vision system was constructed. The spectral vision system can be used to acquire a low dimensional component image set for the two dimensional spectral image reconstruction. The data obtained by the spectral vision system is small and therefore convenient for storing and transmitting a spectral image.

Improving the oscillating grid method to characterize aquaculture biosolids using a laser beam and image analysis

Quickremovalofbiosolidsinaquaculturefacilities,andspeciallyinrecirculatingaquaculturesystems(RAS),isoneofthemostimportantstepinwastemanagement.Sedimentationdynamicsofbiosolidsinanaquaculturetankwilldeterminetheiraccumulationatthebottomofthetank.

The Shadow Moiré method using the phase shifting technique and digital image processing: computational implementation and application to the 3D-reconstruction of a buckled plate

The Shadow Moiré fringe patterns are level lines of equal depth generated by interference between a master grid and its shadow projected on the surface. In simplistic approach, the minimum error is about the order of the master grid pitch, that is, always larger than 0,1 mm, resulting in an experimental technique of low precision. The use of a phase shift increases the accuracy of the Shadow Moiré technique. The current work uses the phase shifting method to determine the surfaces three-dimensional shape using isothamic fringe patterns and digital image processing. The current study presents the method and applies it to images obtained by simulation for error evaluation, as well as to a buckled plate, obtaining excellent results. The method hands itself particularly useful to decrease the errors in the interpretation of the Moiré fringes that can adversely affect the calculations of displacements in pieces containing many concave and convex regions in relatively small areas.

Image analysis and definition of nuclear phenotypes

Some basic topics concerned with the extraction of textural and geometric information from cell nucleus images as well as description and characterization of chromatin supraorganization and consequent classification of nuclear phenotypes are presented.

Measurement of epidermal thickness in a patient with psoriasis by computer-supported image analysis

The aim of the present study was to measure full epidermal thickness, stratum corneum thickness, rete length, dermal papilla widening and suprapapillary epidermal thickness in psoriasis patients using a light microscope and computer-supported image analysis. The data obtained were analyzed in terms of patient age, type of psoriasis, total body surface area involvement, scalp and nail involvement, duration of psoriasis, and family history of the disease. The study was conducted on 64 patients and 57 controls whose skin biopsies were examined by light microscopy. The acquired microscopic images were transferred to a computer and measurements were made using image analysis. The skin biopsies, taken from different body areas, were examined for different parameters such as epidermal, corneal and suprapapillary epidermal thickness. The most prominent increase in thickness was detected in the palmar region. Corneal thickness was more pronounced in patients with scalp involvement than in patients without scalp involvement (t = -2.651, P = 0.008). The most prominent increase in rete length was observed in the knees (median: 491 µm, t = 10.117, P = 0.000). The difference in rete length between patients with a positive and a negative family history was significant (t = -3.334, P = 0.03), being 27% greater in psoriasis patients without a family history. The differences in dermal papilla distances among patients were very small. We conclude that microscope-supported thickness measurements provide objective results.

Optimization of image analysis techniques for quality assessment of whole-wheat breads made with fat replacer

The cellular structure of healthy food products, with added dietary fiber and low in calories, is an important factor that contributes to the assessment of quality, which can be quantified by image analysis of visual texture. This study seeks to compare image analysis techniques (binarization using Otsu’s method and the default ImageJ algorithm, a variation of the iterative intermeans method) for quantification of differences in the crumb structure of breads made with different percentages of whole-wheat flour and fat replacer, and discuss the behavior of the parameters number of cells, mean cell area, cell density, and circularity using response surface methodology. Comparative analysis of the results achieved with the Otsu and default ImageJ algorithms showed a significant difference between the studied parameters. The Otsu method demonstrated the crumb structure of the analyzed breads more reliably than the default ImageJ algorithm, and is thus the most suitable in terms of structural representation of the crumb texture.

Automated static image analysis as a novel tool in describing the physical properties of dietary fiber

Abstract The growing interest in the usage of dietary fiber in food has caused the need to provide precise tools for describing its physical properties. This research examined two dietary fibers from oats and beets, respectively, in variable particle sizes. The application of automated static image analysis for describing the hydration properties and particle size distribution of dietary fiber was analyzed. Conventional tests for water holding capacity (WHC) were conducted. The particles were measured at two points: dry and after water soaking. The most significant water holding capacity (7.00 g water/g solid) was achieved by the smaller sized oat fiber. Conversely, the water holding capacity was highest (4.20 g water/g solid) in larger sized beet fiber. There was evidence for water absorption increasing with a decrease in particle size in regards to the same fiber source. Very strong correlations were drawn between particle shape parameters, such as fiber length, straightness, width and hydration properties measured conventionally. The regression analysis provided the opportunity to estimate whether the automated static image analysis method could be an efficient tool in describing the hydration properties of dietary fiber. The application of the method was validated using mathematical model which was verified in comparison to conventional WHC measurement results.

Automated system of seedling image analysis (SVIS) and electrical conductivity to assess sun hemp seed vigor

The development of new procedures for quickly obtaining accurate information on the physiological potential of seed lots is essential for developing quality control programs for the seed industry. In this study, the effectiveness of an automated system of seedling image analysis (Seed Vigor Imaging System - SVIS) in determining the physiological potential of sun hemp seeds and its relationship with electrical conductivity tests, were evaluated. SVIS evaluations were performed three and four days after sowing and data on the vigor index and the length and uniformity of seedling growth were collected. The electrical conductivity test was made on 50 seed replicates placed in containers with 75 mL of deionised water at 25 ºC and readings were taken after 1, 2, 4, 8 and 16 hours of imbibition. Electrical conductivity measurements at 4 or 8 hours and the use of the SVIS on 3-day old seedlings can effectively detect differences in vigor between different sun hemp seed lots.