28 research outputs found
Text detection and recognition in images and video sequences
Text characters embedded in images and video sequences represents a rich source of information for content-based indexing and retrieval applications. However, these text characters are difficult to be detected and recognized due to their various sizes, grayscale values and complex backgrounds. This thesis investigates methods for building an efficient application system for detecting and recognizing text of any grayscale values embedded in images and video sequences. Both empirical image processing methods and statistical machine learning and modeling approaches are studied in two sub-problems: text detection and text recognition. Applying machine learning methods for text detection encounters difficulties due to character size, grayscale variations and heavy computation cost. To overcome these problems, we propose a two-step localization/verification approach. The first step aims at quickly localizing candidate text lines, enabling the normalization of characters into a unique size. In the verification step, a trained support vector machine or multi-layer perceptrons is applied on background independent features to remove the false alarms. Text recognition, even from the detected text lines, remains a challenging problem due to the variety of fonts, colors, the presence of complex backgrounds and the short length of the text strings. Two schemes are investigated addressing the text recognition problem: bi-modal enhancement scheme and multi-modal segmentation scheme. In the bi-modal scheme, we propose a set of filters to enhance the contrast of black and white characters and produce a better binarization before recognition. For more general cases, the text recognition is addressed by a text segmentation step followed by a traditional optical character recognition (OCR) algorithm within a multi-hypotheses framework. In the segmentation step, we model the distribution of grayscale values of pixels using a Gaussian mixture model or a Markov Random Field. The resulting multiple segmentation hypotheses are post-processed by a connected component analysis and a grayscale consistency constraint algorithm. Finally, they are processed by an OCR software. A selection algorithm based on language modeling and OCR statistics chooses the text result from all the produced text strings. Additionally, methods for using temporal information of video text are investigated. A Monte Carlo video text segmentation method is proposed for adapting the segmentation parameters along temporal text frames. Furthermore, a ROVER (Recognizer Output Voting Error Reduction) algorithm is studied for improving the final recognition text string by voting the characters through temporal frames
Unmet goals of tracking: within-track heterogeneity of students' expectations for
Educational systems are often characterized by some form(s) of ability grouping, like tracking. Although substantial variation in the implementation of these practices exists, it is always the aim to improve teaching efficiency by creating homogeneous groups of students in terms of capabilities and performances as well as expected pathways. If students’ expected pathways (university, graduate school, or working) are in line with the goals of tracking, one might presume that these expectations are rather homogeneous within tracks and heterogeneous between tracks. In Flanders (the northern region of Belgium), the educational system consists of four tracks. Many students start out in the most prestigious, academic track. If they fail to gain the necessary credentials, they move to the less esteemed technical and vocational tracks. Therefore, the educational system has been called a 'cascade system'. We presume that this cascade system creates homogeneous expectations in the academic track, though heterogeneous expectations in the technical and vocational tracks. We use data from the International Study of City Youth (ISCY), gathered during the 2013-2014 school year from 2354 pupils of the tenth grade across 30 secondary schools in the city of Ghent, Flanders. Preliminary results suggest that the technical and vocational tracks show more heterogeneity in student’s expectations than the academic track. If tracking does not fulfill the desired goals in some tracks, tracking practices should be questioned as tracking occurs along social and ethnic lines, causing social inequality
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Cortical and psychophysiological effects of sensory modulation on attentional switching during exercise
The present research programme sought to further understanding of the neurophysiological
mechanisms that underlie the effects of music on exercise. Five original experiments were
conducted using a wide range of psychophysical, psychological, physiological, and
psychophysiological techniques. The results of the first study indicated that music partially
reallocates attention towards task-unrelated thoughts (i.e., external dissociation), suppresses
the amplitude of low-frequency waves in the brain, and enhances task performance. The
findings of the second study indicated that music can have a negative effect if delivered
during the execution of highly-demanding cognitive-motor tasks. In such instances, the right
parietal regions of the brain activate in response to the presence of auditory distractors and
prevent task performance from being compromised. The third study shed new light on the
neural control of working muscles and indicated that music has the potential to reduce the
frequency of electrical outputs emitted to the musculature and reduce the communication
between the central motor command and adjacent regions. The fourth study of this research
programme was conducted in an ecologically valid environment, wherein participants walked
at self-paced speeds in the presence of different auditory stimuli. The results of the fourth
study indicated that music elicits more positive affective responses and up-regulates beta
waves to a greater degree than no-music conditions. Finally, the fifth study of this thesis
made use of functional magnetic resonance imaging to explore the brain regions that activate
in response to exercise and music. The results of this final study revealed that the left inferior
frontal gyrus is highly active when individuals execute part-body exercises with music. The
present research programme provides a neurophysiological basis for the use of music in
exercise settings. The findings presented herein support the use of music as a valuable tool to
explore more complex psychophysiological phenomena such as attention, affect, and fatigue.Brazilian Government (Coordination for the Improvement of Higher Education Personnel [CAPES]