A photographic journey through Vietnam

This degree project consists of “A photographic journey through Vietnam”. One month was spent in Vietnam where the different aspects of the Vietnamese life were documented in images. The journey began in Hanoi and descended down the country to Ho Chi Minh City.The report describes the compositional elements of photography and makes an attempt to describe what a “good” image is. Furthermore it explains what equipment that is necessary for such a journey and how you can interact with the local population.When the journey came to an end, a photographic book consisting of 200 images was created. The report details the used workflow step by step. Finally the author has commented 20 of the selected images regarding their photographic composition.

Print quality study of a laboratory offset press

PAPRO operates within the Forest Research company and their mission is to develop value-addingindustry solutions. At present there are no good ways for mills to easily test the printing quality on newsprintpaper. There is a great need for a fast way to do this on different paper qualities; with a laboratory-offset press this can be both a time and money saving method. At PAPRO Forest Research, NewZealand, a laboratory offset press has been developed and designed, during the past seven years, concerningthis issue. Earlier projects were made concerning the press, e.g. to establish the optimal settings.The mission with this project was to partly determine the present variability of the print quality andto evaluate if the fountain solution, distilled water and 2% Diol green concentrate, used at the momentmixed with different percentages of Isopropanol could decrease the variability and contribute to morestabile results. Throughout the whole project the print quality showed a high variation and was evenmore variable when the Isopropanol was added. All in all 50 print rounds times twelve printed paperstrips was carried out through the project divided into three parts. To analyse the print quality, amicroscope with an image capture camera has been used. Data from the taken images was analysedand inserted into charts to see the variations.The conclusions of the whole project are not satisfying because no final evaluations were possible tomake. Main conclusions are that the additive of Isopropanol to the ordinary fountain solution, used atpresent, only contributed to more unstable results of the print quality. And it seems to be difficult toget some stable results from the lab press as long as the room where it is placed is not fully conditionedas required for the process of offset printing. And the fact that the airbrush which applies theamount of fountain solution is also variable, as shown in earlier projects, which contributes to unstableresults as well. For further work more exact parameters as a conditioned room are required and thepossibility to further design the laboratory press to use waterless offset printing instead.

Characters Extraction for Traffic Sign Destination boards in video and still images

Traffic Control Signs or destination boards on roadways offer significant information for drivers. Regulation signs tell something like your speed, turns, etc; Warning signs warn drivers of conditions ahead to help them avoid accidents; Destination signs show distances and directions to various locations; Service signs display location of hospitals, gas and rest areas etc. Because the signs are so important and there is always a certain distance from them to drivers, to let the drivers get information clearly and easily even in bad weather or other situations. The idea is to develop software which can collect useful information from a special camera which is mounted in the front of a moving car to extract the important information and finally show it to the drivers. For example, when a frame contains on a destination drive sign board it will be text something like "Linkoping 50",so the software should extract every character of "Linkoping 50", compare them with the already known character data in the database. if there is extracted character match "k" in the database then output the destination name and show to the driver. In this project C++ will be used to write the code for this software.

Evaluation of Red Colour Segmentation Algorithms in Traffic Signs Detection

Colour segmentation is the most commonly used method in road signs detection. Road sign contains several basic colours such as red, yellow, blue and white which depends on countries.The objective of this thesis is to do an evaluation of the four colour segmentation algorithms. Dynamic Threshold Algorithm, A Modification of de la Escalera’s Algorithm, the Fuzzy Colour Segmentation Algorithm and Shadow and Highlight Invariant Algorithm. The processing time and segmentation success rate as criteria are used to compare the performance of the four algorithms. And red colour is selected as the target colour to complete the comparison. All the testing images are selected from the Traffic Signs Database of Dalarna University [1] randomly according to the category. These road sign images are taken from a digital camera mounted in a moving car in Sweden.Experiments show that the Fuzzy Colour Segmentation Algorithm and Shadow and Highlight Invariant Algorithm are more accurate and stable to detect red colour of road signs. And the method could also be used in other colours analysis research. The yellow colour which is chosen to evaluate the performance of the four algorithms can reference Master Thesis of Yumei Liu.

Hand Gesture Detection & Recognition System

The project introduces an application using computer vision for Hand gesture recognition. A camera records a live video stream, from which a snapshot is taken with the help of interface. The system is trained for each type of count hand gestures (one, two, three, four, and five) at least once. After that a test gesture is given to it and the system tries to recognize it.A research was carried out on a number of algorithms that could best differentiate a hand gesture. It was found that the diagonal sum algorithm gave the highest accuracy rate. In the preprocessing phase, a self-developed algorithm removes the background of each training gesture. After that the image is converted into a binary image and the sums of all diagonal elements of the picture are taken. This sum helps us in differentiating and classifying different hand gestures.Previous systems have used data gloves or markers for input in the system. I have no such constraints for using the system. The user can give hand gestures in view of the camera naturally. A completely robust hand gesture recognition system is still under heavy research and development; the implemented system serves as an extendible foundation for future work.

Att främja ett ackomodativt lärande utifrån ettandragogiskt perspektiv : I en offentlig organisation

En upplevelse av att det finns begränsade kunskaper kring vuxna individers väg att lära utgörgrunden för denna undersökning. Utbildningar idag kommer ofta i form av föreläsningarvilket framför allt resulterar i ett assimilativt lärande, det vill säga ett ytligt lärande därindividen saknar förståelse för kunskapen. Pedagogik är ett begrepp som överlag i storutsträckning används när lärande är målet oavsett vem som ska lära sig något. Kursupplägg avpedagogisk karaktär vänder sig främst till barn och kan anses olämplig när vuxna individerska lära sig. Andragogik är begreppet för vuxenlärande, vilken bygger på kunskapen om attvuxna är självstyrande individer och behöver därför själva ta steget till att lära sig något nytt. Iden andragogiska modellen presenteras de förutsättningar som krävs för att en vuxen individska kunna tillägna sig nya kunskaper på en djupare nivå, få en förståelse, denna nivå avlärande kallas för ett ackomodativt lärande.Undersökningens syfte var att studera om de två processledarnas ledarskap och kursupplägggrundas i andragogik för att främja ett ackomodativt lärande i Landstinget Dalarnas Chef ochledarprogram.Undersökningen var en fallstudie där en deduktiv ansats förelåg. En kvalitativ metod i formav observation har använts för insamling av data. Processledarna för Chef ochledarprogrammet har observerats och filmats med filmkamera under en av fyra delar av ettintroduktionsblock. Ledarskap och kursupplägg är två områden som behandlas teoretiskt dåde anses kunna påverka lärandet för vuxna personer såväl kollektivt som individuellt.Processledarna för Landstinget Dalarnas Chef och ledarprogram tog i stor utsträckning hänsyntill de vuxna individernas behov, som kan förstås utifrån den andragogiska modellen. Genomsitt ledarskap och kursupplägg skapade de goda förutsättningar för deltagarnas möjlighet attkunna tillägna sig ett ackomodativt lärande. Processledarnas ledarskap grundar sig i känslor,relationer och med människosynen att alla människor har samma grundläggande behov.Kursupplägget bestod av övningar och dialoger där deltagarna involverades, vilketförespråkas i den andragogiska modellen för att kunna uppnå ett ackomodativt lärande

A Computer Vision Framework For Finger-Tapping Evaluation In Parkinson's Disease

Objective: To define and evaluate a Computer-Vision (CV) method for scoring Paced Finger-Tapping (PFT) in Parkinson's disease (PD) using quantitative motion analysis of index-fingers and to compare the obtained scores to the UPDRS (Unified Parkinson's Disease Rating Scale) finger-taps (FT). Background: The naked-eye evaluation of PFT in clinical practice results in coarse resolution to determine PD status. Besides, sensor mechanisms for PFT evaluation may cause patients discomfort. In order to avoid cost and effort of applying wearable sensors, a CV system for non-invasive PFT evaluation is introduced. Methods: A database of 221 PFT videos from 6 PD patients was processed. The subjects were instructed to position their hands above their shoulders besides the face and tap the index-finger against the thumb consistently with speed. They were facing towards a pivoted camera during recording. The videos were rated by two clinicians between symptom levels 0-to-3 using UPDRS-FT. The CV method incorporates a motion analyzer and a face detector. The method detects the face of testee in each video-frame. The frame is split into two images from face-rectangle center. Two regions of interest are located in each image to detect index-finger motion of left and right hands respectively. The tracking of opening and closing phases of dominant hand index-finger produces a tapping time-series. This time-series is normalized by the face height. The normalization calibrates the amplitude in tapping signal which is affected by the varying distance between camera and subject (farther the camera, lesser the amplitude). A total of 15 features were classified using K-nearest neighbor (KNN) classifier to characterize the symptoms levels in UPDRS-FT. The target ratings provided by the raters were averaged. Results: A 10-fold cross validation in KNN classified 221 videos between 3 symptom levels with 75% accuracy. An area under the receiver operating characteristic curves of 82.6% supports feasibility of the obtained features to replicate clinical assessments. Conclusions: The system is able to track index-finger motion to estimate tapping symptoms in PD. It has certain advantages compared to other technologies (e.g. magnetic sensors, accelerometers etc.) for PFT evaluation to improve and automate the ratings

Real time video segmentation for recognising paint marks on bad wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are based on visual analysis. Machine vision based approach has been done to emulate the visual abilities of human operator to enable automation of the process. Through this process bad sleepers are identified, and a spot is marked on it with specific color (blue in the current case) on the rail so that the maintenance operators are able to identify the spot and replace the sleeper. The motive of this thesis is to help the operators to identify those sleepers which are marked by color (spots), using an “Intelligent Vehicle” which is capable of running on the track. Capturing video while running on the track and segmenting the object of interest (spot) through this vehicle; we can automate this work and minimize the human intuitions. The video acquisition process depends on camera position and source light to obtain fine brightness in acquisition, we have tested 4 different types of combinations (camera position and source light) here to record the video and test the validity of proposed method. A sequence of real time rail frames are extracted from these videos and further processing (depending upon the data acquisition process) is done to identify the spots. After identification of spot each frame is divided in to 9 regions to know the particular region where the spot lies to avoid overlapping with noise, and so on. The proposed method will generate the information regarding in which region the spot lies, based on nine regions in each frame. From the generated results we have made some classification regarding data collection techniques, efficiency, time and speed. In this report, extensive experiments using image sequences from particular camera are reported and the experiments were done using intelligent vehicle as well as test vehicle and the results shows that we have achieved 95% success in identifying the spots when we use video as it is, in other method were we can skip some frames in pre-processing to increase the speed of video but the segmentation results we reduced to 85% and the time was very less compared to previous one. This shows the validity of proposed method in identification of spots lying on wooden railway sleepers where we can compromise between time and efficiency to get the desired result.

Traffic and Road Sign Recognition

This thesis presents a system to recognise and classify road and traffic signs for the purpose of developing an inventory of them which could assist the highway engineers’ tasks of updating and maintaining them. It uses images taken by a camera from a moving vehicle. The system is based on three major stages: colour segmentation, recognition, and classification. Four colour segmentation algorithms are developed and tested. They are a shadow and highlight invariant, a dynamic threshold, a modification of de la Escalera’s algorithm and a Fuzzy colour segmentation algorithm. All algorithms are tested using hundreds of images and the shadow-highlight invariant algorithm is eventually chosen as the best performer. This is because it is immune to shadows and highlights. It is also robust as it was tested in different lighting conditions, weather conditions, and times of the day. Approximately 97% successful segmentation rate was achieved using this algorithm.Recognition of traffic signs is carried out using a fuzzy shape recogniser. Based on four shape measures - the rectangularity, triangularity, ellipticity, and octagonality, fuzzy rules were developed to determine the shape of the sign. Among these shape measures octangonality has been introduced in this research. The final decision of the recogniser is based on the combination of both the colour and shape of the sign. The recogniser was tested in a variety of testing conditions giving an overall performance of approximately 88%.Classification was undertaken using a Support Vector Machine (SVM) classifier. The classification is carried out in two stages: rim’s shape classification followed by the classification of interior of the sign. The classifier was trained and tested using binary images in addition to five different types of moments which are Geometric moments, Zernike moments, Legendre moments, Orthogonal Fourier-Mellin Moments, and Binary Haar features. The performance of the SVM was tested using different features, kernels, SVM types, SVM parameters, and moment’s orders. The average classification rate achieved is about 97%. Binary images show the best testing results followed by Legendre moments. Linear kernel gives the best testing results followed by RBF. C-SVM shows very good performance, but ?-SVM gives better results in some case.

Color detection and segmentation for road and traffic signs

This paper aims to present three new methods for color detection and segmentation of road signs. The images are taken by a digital camera mounted in a car. The RGB images are converted into IHLS color space, and new methods are applied to extract the colors of the road signs under consideration. The methods are tested on hundreds of outdoor images in different light conditions, and they show high robustness. This project is part of the research taking place in Dalarna University / Sweden in the field of the ITS.

Utveckling av metod för att bedöma behovet av ogräsbekämpning i spår

A system for weed management on railway embankments that is both adapted to the environment and efficient in terms of resources requires knowledge and understanding about the growing conditions of vegetation so that methods to control its growth can be adapted accordingly. Automated records could complement present-day manual inspections and over time come to replace these. One challenge is to devise a method that will result in a reasonable breakdown of gathered information that can be managed rationally by affected parties and, at the same time, serve as a basis for decisions with sufficient precision. The project examined two automated methods that may be useful for the Swedish Transport Administration in the future: 1) A machine vision method, which makes use of camera sensors as a way of sensing the environment in the visible and near infrared spectrum; and 2) An N-Sensor method, which transmits light within an area that is reflected by the chlorophyll in the plants. The amount of chlorophyll provides a value that can be correlated with the biomass. The choice of technique depends on how the information is to be used. If the purpose is to form a general picture of the growth of vegetation on railway embankments as a way to plan for maintenance measures, then the N-Sensor technique may be the right choice. If the plan is to form a general picture as well as monitor and survey current and exact vegetation status on the surface over time as a way to fight specific vegetation with the correct means, then the machine vision method is the better of the two. Both techniques involve registering data using GPS positioning. In the future, it will be possible to store this information in databases that are directly accessible to stakeholders online during or in conjunction with measures to deal with the vegetation. The two techniques were compared with manual (visual) estimations as to the levels of vegetation growth. The observers (raters) visual estimation of weed coverage (%) differed statistically from person to person. In terms of estimating the frequency (number) of woody plants (trees and bushes) in the test areas, the observers were generally in agreement. The same person is often consistent in his or her estimation: it is the comparison with the estimations of others that can lead to misleading results. The system for using the information about vegetation growth requires development. The threshold for the amount of weeds that can be tolerated in different track types is an important component in such a system. The classification system must be capable of dealing with the demands placed on it so as to ensure the quality of the track and other pre-conditions such as traffic levels, conditions pertaining to track location, and the characteristics of the vegetation. The project recommends that the Swedish Transport Administration: Discusses how threshold values for the growth of vegetation on railway embankments can be determined Carries out registration of the growth of vegetation over longer and a larger number of railway sections using one or more of the methods studied in the project Introduces a system that effectively matches the information about vegetation to its position Includes information about the growth of vegetation in the records that are currently maintained of the track’s technical quality, and link the data material to other maintenance-related databases Establishes a number of representative surfaces in which weed inventories (by measuring) are regularly conducted, as a means of developing an overview of the long-term development that can serve as a basis for more precise prognoses in terms of vegetation growth Ensures that necessary opportunities for education are put in place