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.

Fingerprint Segmentation

In this thesis, a new algorithm has been proposed to segment the foreground of the fingerprint from the image under consideration. The algorithm uses three features, mean, variance and coherence. Based on these features, a rule system is built to help the algorithm to efficiently segment the image. In addition, the proposed algorithm combine split and merge with modified Otsu. Both enhancements techniques such as Gaussian filter and histogram equalization are applied to enhance and improve the quality of the image. Finally, a post processing technique is implemented to counter the undesirable effect in the segmented image. Fingerprint recognition system is one of the oldest recognition systems in biometrics techniques. Everyone have a unique and unchangeable fingerprint. Based on this uniqueness and distinctness, fingerprint identification has been used in many applications for a long period. A fingerprint image is a pattern which consists of two regions, foreground and background. The foreground contains all important information needed in the automatic fingerprint recognition systems. However, the background is a noisy region that contributes to the extraction of false minutiae in the system. To avoid the extraction of false minutiae, there are many steps which should be followed such as preprocessing and enhancement. One of these steps is the transformation of the fingerprint image from gray-scale image to black and white image. This transformation is called segmentation or binarization. The aim for fingerprint segmentation is to separate the foreground from the background. Due to the nature of fingerprint image, the segmentation becomes an important and challenging task. The proposed algorithm is applied on FVC2000 database. Manual examinations from human experts show that the proposed algorithm provides an efficient segmentation results. These improved results are demonstrating in diverse experiments.

Color Segmentation using LVQ-Learning Vector Quantization

This thesis aims to present a color segmentation approach for traffic sign recognition based on LVQ neural networks. The RGB images were converted into HSV color space, and segmented using LVQ depending on the hue and saturation values of each pixel in the HSV color space. LVQ neural network was used to segment red, blue and yellow colors on the road and traffic signs to detect and recognize them. LVQ was effectively applied to 536 sampled images taken from different countries in different conditions with 89% accuracy and the execution time of each image among 31 images was calculated in between 0.726sec to 0.844sec. The method was tested in different environmental conditions and LVQ showed its capacity to reasonably segment color despite remarkable illumination differences. The results showed high robustness.

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.

Quelques réflexions sur les origines de l'argot français du XXe siècle

Le but de ce mémoire est d’étudier les origines étymologiques des mots argotiques qui ont commencé à être utilisés pendant le vingtième siècle. 100 mots ont été choisis et présentés selon leurs origines. Les mots ont été choisis dans le Dictionnaire de l’argot et du français populaire. Les langues d’origine les plus représentées parmi ces 100 mots ont été étudiées pour voir s’il y a une raison probable pour laquelle le français a emprunté des mots à ces langues. Nous avons classé la plupart des mots en champs lexicaux pour examiner s’il y a un certain type de mots qui sont empruntés et si les langues différentes contribuent à des champs lexicaux différents. L’étude a montré que le français a emprunté des mots argotiques aux beaucoup de langues différentes pendant le vingtième siècle. L’anglais et l’arabe ont contribué avec le plus grand nombre de mots. Pour ces deux langues et pour la plupart des autres langues de l’étude, nous discutons des raisons possibles pour lesquelles les mots ont été empruntés.

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.

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.

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.