Road and Traffic Signs Recognition using Vector Machines

Intelligent Transportation System (ITS) is a system that builds a safe, effective and integrated transportation environment based on advanced technologies. Road signs detection and recognition is an important part of ITS, which offer ways to collect the real time traffic data for processing at a central facility.This project is to implement a road sign recognition model based on AI and image analysis technologies, which applies a machine learning method, Support Vector Machines, to recognize road signs. We focus on recognizing seven categories of road sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for training and test. We compared and analyzed the performances of SVM recognition model using different features and different kernels. Moreover, the performances using different recognition models, SVM and Fuzzy ARTMAP, are observed.

Gloss and gloss variations inelectrophotographic print = Glans och glansvariationer i elektrofotografiskt tryck

This degree project was performed at M-real Technology Centre in Örnsköldsvik. The perpose was to investigate thedifferences in gloss and gloss variations between chemical and ground toner and different paper grades in electrophotographicprints. Gloss is a property that gives the impression of a higher quality of a product. Therefore it is of great importance toaccomplish high gloss in advertising print.A test chart was printed on three different uncoated paper grades on three different printers. Thereafter, gloss, glossvariation, surface topography, print mottle and density were measured. A visual evalution was also performed. A multivariateanalysis was acheived of the data in order to find correlations between the measured variations.The results showed that paper grades with large surface roughness gave more variations in surface topography and glossvariations (both visual and measured) in print. A rough surface also gave more print mottle. Ground toner gave moresurface topography variations and mottle which increased with the amount of silicone used.

Obstacles and Opportunities Foreign Graduates Meet In Dalarna Labour Market, Sweden

Foreign graduates have been part of the success stories of many developed countries. This is as a result of their immeasurable deposit of ideas, knowledge, and innovation in the host country. Though the process of these foreign graduates penetrating and integrating into the labour market of the host country could be slow and rough as they encounter some obstacles on the way; they still strive to break through and be part of the country’s workforce because they foresee some opportunities therein. This research study is about the obstacles and opportunities foreign graduates meet in Dalarna labour market. The study investigated and identified the obstacles and opportunities foreign graduates meet in Dalarna labour market. For a thorough execution of this research, we collected primary data by handing questionnaires to 65 foreign graduates searching for jobs in Dalarna region and interviewed eight people, among which seven were foreign graduates and one of them was a staff at Arbestförmedlingen (Employment Agency) to give us a general view of the Dalarna labour market. We read previous research works and related articles to understand the topic in order to get an overview of the terminologies and concept to apply. This study concluded that language is a major obstacle foreign graduates meet in the Dalarna labour market. Other possible obstacles include culture, poor integration policies, lack of a placement bureau, lack of trust, limited opportunities, favoritism, lack of jobs, lack of references and experience. On the other hand factors like job availability, outgoing labour force and unskilled labour are possible opportunities foreign graduates meet in the Dalarna labour market. Furthermore flexible work time, good working atmosphere, experience, social security/welfare, good standard of living, family friendly region, higher wages, job security and cheap cost of living are also possible benefits that foreign graduates get in Dalarna.

IT­-Forensisk undersökning av flyktigt minne : På Linux och Android enheter

Att kunna gör en effektiv undersökning av det flyktiga minnet är något som blir viktigare ochviktigare i IT-forensiska utredningar. Dels under Linux och Windows baserade PC installationermen också för mobila enheter i form av Android och enheter baserade andra mobila opperativsy-stem.Android använder sig av en modifierad Linux-kärna var modifikationer är för att anpassa kärnantill de speciella krav som gäller för ett mobilt operativsystem. Dessa modifikationer innefattardels meddelandehantering mellan processer men även ändringar till hur internminnet hanteras ochövervakas.Då dessa två kärnor är så pass nära besläktade kan samma grundläggande principer användas föratt dumpa och undersöka minne. Dumpningen sker via en kärn-modul vilket i den här rapportenutgörs av en programvara vid namn LiME vilken kan hantera bägge kärnorna.Analys av minnet kräver att verktygen som används har en förståelse för minneslayouten i fråga.Beroende på vilken metod verktyget använder så kan det även behövas information om olika sym-boler. Verktyget som används i det här examensarbetet heter Volatility och klarar på papperet avatt extrahera all den information som behövs för att kunna göra en korrekt undersökning.Arbetet avsåg att vidareutveckla existerande metoder för analys av det flyktiga minnet på Linux-baserade maskiner (PC) och inbyggda system(Android). Problem uppstod då undersökning avflyktigt minne på Android och satta mål kunde inte uppnås fullt ut. Det visade sig att minnesanalysriktat emot PC-plattformen är både enklare och smidigare än vad det är mot Android.

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.