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.

Road Sign Recognition based onInvariant Features using SupportVector Machine

Since last two decades researches have been working on developing systems that can assistsdrivers in the best way possible and make driving safe. Computer vision has played a crucialpart in design of these systems. With the introduction of vision techniques variousautonomous and robust real-time traffic automation systems have been designed such asTraffic monitoring, Traffic related parameter estimation and intelligent vehicles. Among theseautomatic detection and recognition of road signs has became an interesting research topic.The system can assist drivers about signs they don’t recognize before passing them.Aim of this research project is to present an Intelligent Road Sign Recognition System basedon state-of-the-art technique, the Support Vector Machine. The project is an extension to thework done at ITS research Platform at Dalarna University [25]. Focus of this research work ison the recognition of road signs under analysis. When classifying an image its location, sizeand orientation in the image plane are its irrelevant features and one way to get rid of thisambiguity is to extract those features which are invariant under the above mentionedtransformation. These invariant features are then used in Support Vector Machine forclassification. Support Vector Machine is a supervised learning machine that solves problemin higher dimension with the help of Kernel functions and is best know for classificationproblems.

Prosodic Morphology : Gender in Arabic Perfect Active and Passive 3rd Person Singular Verbs

Prosodic /template Morphology, that "draws heavily on the theoretical apparatus and formalisms of the generative phonology model known as autosegmental phonology" (Katamba, F. 1993: 154), is the best analysis that can handle Arabic morphology. Verbs in Arabic are represented on three independent tiers: root tier, the skeletal tier and the vocalic melody tier (Katamba, F. 1993). Vowel morphemes, which are represented by diacritics, are inserted within the consonant morphemes, which are represented by primary symbols, to form words. The morpheme tier hypothesis paves the way to understand the nonconcatenative Arabic morphology. This paper analyzes gender in perfect active and passive 3rd person singular verbs on the basis of PM. The focus of the analysis shall be drawn heavily on the most common Arabic verbs; triconsonantal verbs, with brief introduction of the less common verbs; quadriconsonantal perfect active and passive masculine and feminine 3rd person singular verbs. I shall, too, cast the light on some vowel changes that some verbs undergo when voice changes.

Real-Time Recognition System for Traffic Signs

The aim of this thesis project is to develop the Traffic Sign Recognition algorithm for real time. Inreal time environment, vehicles move at high speed on roads. For the vehicle intelligent system itbecomes essential to detect, process and recognize the traffic sign which is coming in front ofvehicle with high relative velocity, at the right time, so that the driver would be able to pro-actsimultaneously on instructions given in the Traffic Sign. The system assists drivers about trafficsigns they did not recognize before passing them. With the Traffic Sign Recognition system, thevehicle becomes aware of the traffic environment and reacts according to the situation.The objective of the project is to develop a system which can recognize the traffic signs in real time.The three target parameters are the system’s response time in real-time video streaming, the trafficsign recognition speed in still images and the recognition accuracy. The system consists of threeprocesses; the traffic sign detection, the traffic sign recognition and the traffic sign tracking. Thedetection process uses physical properties of traffic signs based on a priori knowledge to detect roadsigns. It generates the road sign image as the input to the recognition process. The recognitionprocess is implemented using the Pattern Matching algorithm. The system was first tested onstationary images where it showed on average 97% accuracy with the average processing time of0.15 seconds for traffic sign recognition. This procedure was then applied to the real time videostreaming. Finally the tracking of traffic signs was developed using Blob tracking which showed theaverage recognition accuracy to 95% in real time and improved the system’s average response timeto 0.04 seconds. This project has been implemented in C-language using the Open Computer VisionLibrary.

An Upgrade of Network Traffic Recognition System for SIP/VoIP Traffic Recognition

The purpose of this project is to update the tool of Network Traffic Recognition System (NTRS) which is proprietary software of Ericsson AB and Tsinghua University, and to implement the updated tool to finish SIP/VoIP traffic recognition. Basing on the original NTRS, I analyze the traffic recognition principal of NTRS, and redesign the structure and module of the tool according to characteristics of SIP/VoIP traffic, and then finally I program to achieve the upgrade. After the final test with our SIP data trace files in the updated system, a satisfactory result is derived. The result presents that our updated system holds a rate of recognition on a confident level in the SIP session recognition as well as the VoIP call recognition. In the comparison with the software of Wireshark, our updated system has a result which is extremely close to Wireshark’s output, and the working time is much less than Wireshark. In the aspect of practicability, the memory overflow problem is avoided, and the updated system can output the specific information of SIP/VoIP traffic recognition, such as SIP type, SIP state, VoIP state, etc. The upgrade fulfills the demand of this project.

Att vara familjemedlem till en person med schizofreni : En litteraturstudie utifrån familjens perspektiv

Syftet var att utifrån familjemedlemmars perspektiv, beskriva upplevelser och hantering av att ha en familjemedlem med diagnosen schizofreni. Metoden tillämpades till vald design, där material till litteraturstudien söktes via databaserna Cinahl, MEDLINE och PsycINFO. Studiens underlag bestod av 13 artiklar av både kvalitativ och kombinerad ansats, som efter granskning och analys valdes till resultat. Resultatet presenterades genom två kategorier följt av fem subkategorier och visade att sjukdomens medförda beteendeförändring upplevdes som förlust av den person den drabbade en gång var. Känslor som förvirring och förtvivlan upplevdes till följd av den drabbades främmande personlighet. Situationen uppgavs som känslomässigt komplicerad, med svårighet att göra tillståndet begripligt och hanterbart. I takt med sjukdomens utveckling, upplevdes den drabbades förmåga till självständighet minska. Ansvaret att stötta den drabbade, föll på familjemedlemmarna som uppgav svårigheter med att uppnå en tillfredställande balans i vardagen. Känslor som skuld, hopplöshet och enorm belastning upplevdes till följd av ansvaret att försöka tillmötesgå den drabbades och övriga familjemedlemmars behov, samtidigt som de försökte förhindra brutna band inom familjen. Sjukdomen upplevdes påverka hela familjen och inte enbart den drabbade. För att kunna leva med den omfattande förändring som sjukdomen medförde, uppgav familjemedlemmarna vikten och behovet av stöd både inom och utanför familjen.

Anhörigas upplevelser i samband med vård av en äldre person i hemmet : En litteraturöversikt

SAMMANFATTNINGSyftet: Syftet med denna systematiska litteraturstudie var att studera hur anhöriga till äldre personer upplevde sin situation i i samband med att de vårdade sina äldre hemma, hur de hanterade sin situation, samt vilka strategier de använde sig av för att hantera sin roll som anhörigvårdare. Metod: Databaserna Cinahl och Medline användes i sökningarna efter relevanta artiklar. Sökord som användes var relative and older people and home care, home health care and family caregiver elderly people, family caregivers and care givers of aging people, elderly people and family care givers of aging people, family care givers of older people, family caregivers and frail elderly, family caregiver and older people and home care, home care older people and family caregivers older people, family caregivers older people. Efter genomläsning bedömdes 16 artiklar vara användbara i resultatet. Dessa kom från vetenskapliga tidskrifter och artiklarna innehöll både kvalitativa studier som kvantitativa studier. Resultat: De flesta anhörigvårdare var kvinnor, de kunde uppleva en högre belastning än män. De anhöriga påverkades både mentalt, fysiskt och emotionellt. De kände sig bundna men kunde även känna ett välbefinnande i vården av den äldre personen. Anhöriga upplevde sin roll som anhörigvårdare till äldre personer i hemmen som att de var delaktiga i omsorgen genom praktiskt som känslomässigt stöd. Deras situation hade även inverkan på deras upplevelse av stress och hur de hanterade situationen. En del äldre anhörigvårdare var själva äldre och i behov av hjälp. Konsekvenserna av deras reaktioner/upplevelser beskrevs som både subjektiv och objektiv belastning. Samt att de även var mindre benägna att söka stöd i form av avlastning för sina äldre personer. Slutsats: Rollen som anhörigvårdare till äldre personer som vårdas i hemmen innebar förändringar i anhörigas livssituation, de fick ta ett stort ansvar för den äldre personen. De upplevde stora påfrestningar både känslomässigt som praktiskt, många kände sig ensamma utan stöd, andra hade olika sätt att hantera sin situation. Äldre anhörigvårdare var mer utsatta för belastning av olika skäl när de vårdade äldre personer i hemmet, dels var de själva äldre samt att de själva kunde vara i behov av hjälp för sina hälsoproblem. Kvinnorna var den grupp anhörigvårdare som upplevde störst belastning i vården av äldre personer i hemmet. När det gällde att söka hjälp och stöd såg det olika ut bland anhörigvårdarna, trots att kvinnorna upplevde störst belastning var de minst benägna att söka hjälp.

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.

Animalism and Person as a Basic Sort

In this paper Animalism is analysed. It will be argued that Animalism is correct in claiming (i) that being of a certain sort of animal S is a fundamental individuative substance sortal concept (animal of the species Homo Sapiens), (ii) that this implies that Animalism is correct in claiming that persons such as us are, by necessity, human beings, (iii) that remaining the same animal is a necessary condition for our identity over time. Contrary to Animalism it will be argued that this does not imply that person should be understood as a phased sortal concept. It will be argued that Animalism rests upon a prior conception of person, and that this implies that person must be understood as a basic substance sortal concept through which we have to individuate ourselves and others. It is further argued that this, together with the insights of Animalism, implies that persons, by necessity, are beings of a biological nature.

Motion Cues Analysis for Parkinson Gait Recognition

Background: Previous assessment methods for PG recognition used sensor mechanisms for PG that may cause discomfort. In order to avoid stress of applying wearable sensors, computer vision (CV) based diagnostic systems for PG recognition have been proposed. Main constraints in these methods are the laboratory setup procedures: Novel colored dresses for the patients were specifically designed to segment the test body from a specific colored background. Objective: To develop an image processing tool for home-assessment of Parkinson Gait(PG) by analyzing motion cues extracted during the gait cycles. Methods: The system is based on the idea that a normal body attains equilibrium during the gait by aligning the body posture with the axis of gravity. Due to the rigidity in muscular tone, persons with PD fail to align their bodies with the axis of gravity. The leaned posture of PD patients appears to fall forward. Whereas a normal posture exhibits a constant erect posture throughout the gait. Patients with PD walk with shortened stride angle (less than 15 degrees on average) with high variability in the stride frequency. Whereas a normal gait exhibits a constant stride frequency with an average stride angle of 45 degrees. In order to analyze PG, levodopa-responsive patients and normal controls were videotaped with several gait cycles. First, the test body is segmented in each frame of the gait video based on the pixel contrast from the background to form a silhouette. Next, the center of gravity of this silhouette is calculated. This silhouette is further skeletonized from the video frames to extract the motion cues. Two motion cues were stride frequency based on the cyclic leg motion and the lean frequency based on the angle between the leaned torso tangent and the axis of gravity. The differences in the peaks in stride and lean frequencies between PG and normal gait are calculated using Cosine Similarity measurements. Results: High cosine dissimilarity was observed in the stride and lean frequencies between PG and normal gait. High variations are found in the stride intervals of PG whereas constant stride intervals are found in the normal gait. Conclusions: We propose an algorithm as a source to eliminate laboratory constraints and discomfort during PG analysis. Installing this tool in a home computer with a webcam allows assessment of gait in the home environment.

What affects recognition most – wrong wordstress or wrong word accent?

In an attempt to find out which of the two Swedish prosodic contrasts of 1) wordstress pattern and 2) tonal word accent category has the greatest communicative weight, a lexical decision experiment was conducted: in one part word stress pattern was changed from trochaic to iambic, and in the other part trochaic accentII words were changed to accent I.Native Swedish listeners were asked to decide whether the distorted words werereal words or ‘non-words’. A clear tendency is that listeners preferred to give more‘non-word’ responses when the stress pattern was shifted, compared to when wordaccent category was shifted. This could have implications for priority of phonological features when teaching Swedish as a second language.

Familjemedlem till person med psykossjukdom : bemötande och utanförskap i psykiatrisk vård

This thesis focused on the situation of family members of persons with psychotic illness, particular on their experience of the approach of the healthcare professionals and of their feelings of alienation regarding the professional care of their family member. A further aim was to explore how siblings who have participated in a support group for siblings experienced their situation. A questionnaire was developed that enabled the aims of this thesis to be investigated (I). Seventy family members from various parts of Sweden participated, and data were collected via the questionnaire developed in study I (II-III). Thirteen siblings who previously had participated in a support group participated in follow-up focus groups interviews (IV). The questionnaire developed was shown to be reliable and valid in these studies (I). In many cases, the participants had experienced an approach from professionals that indicated that they did not experience openness, confirmation and cooperation, and that they felt powerless and socially isolated in relation to the care. There was also found to be a certain degree of association between how the participants experienced the approach and whether they felt alienation (II). The majority of the participants considered openness, confirmation, and cooperation to be important aspects of professional’s approach. The result also identified a low level of agreement between the participants’ experience and what they considered to be significant in the professional’s approach (III). The findings revealed the complexity of being a sibling of an individual with psychotic illness. Participating in a support group for siblings can be of importance in gaining knowledge and minimizing feelings of being alone (IV). Although the psychiatric care services in Sweden have been aware of the importance of cooperating with family members, the results indicated that there is a need for further research in this area.

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.

Motion cue analysis for parkinsonian gait recognition

This paper presents a computer-vision based marker-free method for gait-impairment detection in Patients with Parkinson's disease (PWP). The system is based upon the idea that a normal human body attains equilibrium during the gait by aligning the body posture with Axis-of-Gravity (AOG) using feet as the base of support. In contrast, PWP appear to be falling forward as they are less-able to align their body with AOG due to rigid muscular tone. A normal gait exhibits periodic stride-cycles with stride-angle around 45o between the legs, whereas PWP walk with shortened stride-angle with high variability between the stride-cycles. In order to analyze Parkinsonian-gait (PG), subjects were videotaped with several gait-cycles. The subject's body was segmented using a color-segmentation method to form a silhouette. The silhouette was skeletonized for motion cues extraction. The motion cues analyzed were stride-cycles (based on the cyclic leg motion of skeleton) and posture lean (based on the angle between leaned torso of skeleton and AOG). Cosine similarity between an imaginary perfect gait pattern and the subject gait patterns produced 100% recognition rate of PG for 4 normal-controls and 3 PWP. Results suggested that the method is a promising tool to be used for PG assessment in home-environment.