TY - THES A1 - Vorbach, Paul T1 - Analysen und Heuristiken zur Verbesserung von OCR-Ergebnissen bei Frakturtexten T1 - Analyses and Heuristics for the Improvement of Optical Character Recognition Results for Fraktur Texts N2 - Zahlreiche Digitalisierungsprojekte machen das Wissen vergangener Jahrhunderte jederzeit verfügbar. Das volle Potenzial der Digitalisierung von Dokumenten entfaltet sich jedoch erst, wenn diese als durchsuchbare Volltexte verfügbar gemacht werden. Mithilfe von OCR-Software kann die Erfassung weitestgehend automatisiert werden. Fraktur war ab dem 16. Jahrhundert bis zur Mitte des 20. Jahrhunderts die verbreitete Schrift des deutschen Sprachraums. Durch einige Besonderheiten von Fraktur bleiben die Erkennungsraten bei Frakturtexten aber meist deutlich hinter den Erkennungsergebnissen bei Antiquatexten zurück. Diese Arbeit konzentriert sich auf die Verbesserung der Erkennungsergebnisse der OCR-Software Tesseract bei Frakturtexten. Dazu wurden die Software und bestehende Sprachpakete gesondert auf die Eigenschaften von Fraktur hin analysiert. Durch spezielles Training und Anpassungen an der Software wurde anschließend versucht, die Ergebnisse zu verbessern und Erkenntnisse über die Effektivität verschiedener Ansätze zu gewinnen. Die Zeichenfehlerraten konnten durch verschiedene Experimente von zuvor 2,5 Prozent auf 1,85 Prozent gesenkt werden. Außerdem werden Werkzeuge vorgestellt, die das Training neuer Schriftarten für Tesseract erleichtern und eine Evaluation der erzielten Verbesserungen ermöglichen. N2 - The knowledge of past centuries is made available by numerous digitization projects. However, the full potential of document digitization only unfolds when those are made available as searchable full texts. Capturing this data can be mostly automatized by using OCR software. Fraktur was the most common typeface between the 16th and 20th centuries. The special characteristics of Fraktur usually cause the recognition rates for these texts to be much worse than those for Antiqua texts. This thesis concentrates on improving the recognition rates of the OCR software Tesseract for Fraktur texts. Therefore, the software as well as several language files has been analyzed regarding the special features of Fraktur. By training the software for Fraktur and by adjusting the software itself we tried to improve recognition results and to gain insights about the effectivity of different approaches. During the course of this work, the character error rates were reduced from 2.5 percent to 1.85 percent. Additionally, tools are being presented, which simplify the process of training Tesseract and which allow the user to evaluate the improvements achieved. KW - Optische Zeichenerkennung KW - Klassifikation KW - Frakturschrift KW - OCR KW - Tesseract Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-106527 ER - TY - THES A1 - Sieber, Christian T1 - Holistic Evaluation of Novel Adaptation Logics for DASH and SVC T1 - Leistungsbewertung neuartiger Adaptionslogiken für DASH mit SVC N2 - Streaming of videos has become the major traffic generator in today's Internet and the video traffic share is still increasing. According to Cisco's annual Visual Networking Index report, in 2012, 60% of the global Internet IP traffic was generated by video streaming services. Furthermore, the study predicts further increase to 73% by 2017. At the same time, advances in the fields of mobile communications and embedded devices lead to a widespread adoption of Internet video enabled mobile and wireless devices (e.g. Smartphones). The report predicts that by 2017, the traffic originating from mobile and wireless devices will exceed the traffic from wired devices and states that mobile video traffic was the source of roughly half of the mobile IP traffic at the end of 2012. With the increasing importance of Internet video streaming in today's world, video content provider find themselves in a highly competitive market where user expectations are high and customer loyalty depends strongly on the user's satisfaction with the provided service. In particular paying customers expect their viewing experience to be the same across all their viewing devices and independently of their currently utilized Internet access technology. However, providing video streaming services is costly in terms of storage space, required bandwidth and generated traffic. Therefore, content providers face a trade-off between the user perceived Quality of Experience (QoE) and the costs for providing the service. Today, a variety of transport and application protocols exist for providing video streaming services, but the one utilized depends on the scenario in mind. Video streaming services can be divided up in three categories: Video conferencing, IPTV and Video-on-Demand services. IPTV and video-conferencing have severe real-time constraints and thus utilize mostly datagram-based protocols like the RTP/UDP protocol for the video transmission. Video-on-Demand services in contrast can profit from pre-encoded content, buffers at the end user's device, and mostly utilize TCP-based protocols in combination with progressive streaming for the media delivery. In recent years, the HTTP protocol on top of the TCP protocol gained widespread popularity as a cost-efficient way to distribute pre-encoded video content to customers via progressive streaming. This is due to the fact that HTTP-based video streaming profits from a well-established infrastructure which was originally implemented to efficiently satisfy the increasing demand for web browsing and file downloads. Large Content Delivery Networks (CDN) are the key components of that distribution infrastructure. CDNs prevent expensive long-haul data traffic and delays by distributing HTTP content to world-wide locations close to the customers. As of 2012, already 53% of the global video traffic in the Internet originates from Content Delivery Networks and that percentage is expected to increase to 65% by the year 2017. Furthermore, HTTP media streaming profits from existing HTTP caching infrastructure, ease of NAT and proxy traversal and firewall friendliness. Video delivery through heterogeneous wired and wireless communications networks is prone to distortions due to insufficient network resources. This is especially true in wireless scenarios, where user mobility and insufficient signal strength can result in a very poor transport service performance (e.g. high packet loss, delays and low and varying bandwidth). A poor performance of the transport in turn may degrade the Quality of Experience as perceived by the user, either due to buffer underruns (i.e. playback interruptions) for TCP-based delivery or image distortions for datagram-based real-time video delivery. In order to overcome QoE degradations due to insufficient network resources, content provider have to consider adaptive video streaming. One possibility to implement this for HTTP/TCP streaming is by partitioning the content into small segments, encode the segments into different quality levels and provide access to the segments and the quality level details (e.g. resolution, average bitrate). During the streaming session, a client-centric adaptation algorithm can use the supplied details to adapt the playback to the current environment. However, a lack of a common HTTP adaptive streaming standard led to multiple proprietary solutions developed by major Internet companies like Microsoft (Smooth Streaming), Apple (HTTP Live Streaming) and Adobe (HTTP Dynamic Streaming) loosely based on the aforementioned principle. In 2012, the ISO/IEC published the Dynamic Adaptive Streaming over HTTP (MPEG-DASH) standard. As of today, DASH is becoming widely accepted with major companies announcing their support or having already implemented the standard into their products. MPEG-DASH is typically used with single layer codecs like H.264/AVC, but recent publications show that scalable video coding can use the existing HTTP infrastructure more efficiently. Furthermore, the layered approach of scalable video coding extends the adaptation options for the client, since already downloaded segments can be enhanced at a later time. The influence of distortions on the perceived QoE for non-adaptive video streaming are well reviewed and published. For HTTP streaming, the QoE of the user is influenced by the initial delay (i.e. the time the client pre-buffers video data) and the length and frequency of playback interruptions due to a depleted video playback buffer. Studies highlight that even low stalling times and frequencies have a negative impact on the QoE of the user and should therefore be avoided. The first contribution of this thesis is the identification of QoE influence factors of adaptive video streaming by the means of crowd-sourcing and a laboratory study. MPEG-DASH does not specify how to adapt the playback to the available bandwidth and therefore the design of a download/adaptation algorithm is left to the developer of the client logic. The second contribution of this thesis is the design of a novel user-centric adaption logic for DASH with SVC. Other download algorithms for segmented HTTP streaming with single layer and scalable video coding have been published lately. However, there is little information about the behavior of these algorithms regarding the identified QoE-influence factors. The third contribution is a user-centric performance evaluation of three existing adaptation algorithms and a comparison to the proposed algorithm. In the performance evaluation we also evaluate the fairness of the algorithms. In one fairness scenario, two clients deploy the same adaptation algorithm and share one Internet connection. For a fair adaptation algorithm, we expect the behavior of the two clients to be identical. In a second fairness scenario, one client shares the Internet connection with a large HTTP file download and we expect an even bandwidth distribution between the video streaming and the file download. The forth contribution of this thesis is an evaluation of the behavior of the algorithms in a two-client and HTTP cross traffic scenario. The remainder of this thesis is structured as follows. Chapter II gives a brief introduction to video coding with H.264, the HTTP adaptive streaming standard MPEG-DASH, the investigated adaptation algorithms and metrics of Quality of Experience (QoE) for video streaming. Chapter III presents the methodology and results of the subjective studies conducted in the course of this thesis to identify the QoE influence factors of adaptive video streaming. In Chapter IV, we introduce the proposed adaptation algorithm and the methodology of the performance evaluation. Chapter V highlights the results of the performance evaluation and compares the investigated adaptation algorithms. Section VI summarizes the main findings and gives an outlook towards QoE-centric management of DASH with SVC. KW - DASH KW - DASH KW - SVC KW - crowdsourcing KW - quality of experience KW - qoe KW - progressive download KW - dynamic adaptive streaming over http Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-92362 ER - TY - THES A1 - Kaempgen, Benedikt T1 - Deskriptives Data-Mining für Entscheidungsträger: Eine Mehrfachfallstudie T1 - Descriptive data mining for decision-makers: a multiple case study N2 - Das Potenzial der Wissensentdeckung in Daten wird häufig nicht ausgenutzt, was hauptsächlich auf Barrieren zwischen dem Entwicklerteam und dem Endnutzer des Data-Mining zurückzuführen ist. In dieser Arbeit wird ein transparenter Ansatz zum Beschreiben und Erklären von Daten für Entscheidungsträger vorgestellt. In Entscheidungsträger-zentrierten Aufgaben werden die Projektanforderungen definiert und die Ergebnisse zu einer Geschichte zusammengestellt. Eine Anforderung besteht dabei aus einem tabellarischen Bericht und ggf. Mustern in seinem Inhalt, jeweils verständlich für einen Entscheidungsträger. Die technischen Aufgaben bestehen aus einer Datenprüfung, der Integration der Daten in einem Data-Warehouse sowie dem Generieren von Berichten und dem Entdecken von Mustern wie in den Anforderungen beschrieben. Mehrere Data-Mining-Projekte können durch Wissensmanagement sowie eine geeignete Infrastruktur voneinander profitieren. Der Ansatz wurde in zwei Projekten unter Verwendung von ausschließlich Open-Source-Software angewendet. N2 - Despite high potential of data mining in business and science many projects fail due to barriers between the developer team and the end user. In this work a more transparent approach to describing and explaining data to a decision-maker is presented. In decision-maker-centric tasks project requirements are defined and finally the results composed to a story. A requirement is made of a tabular report and possibly patterns in its data, each understandable to a decision-maker. The technical tasks consist of a data assay, the integration of data within a data warehouse and, as required, the creation of reports and the discovery of patterns. Multiple data mining projects benefit from each other through knowledge management and a common infrastructure. The approach has been applied to two projects exclusively using open source systems. KW - Data Mining KW - Entscheidungsträger KW - Fallstudie KW - Methodologie KW - Endnutzer KW - Business Intelligence KW - Open Source KW - data mining KW - case study KW - process model KW - end user KW - open source Y1 - 2009 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-46343 ER - TY - THES A1 - Höhn, Winfried T1 - Mustererkennung in Frühdrucken T1 - Pattern Perception in Early Printed Books N2 - No abstract available KW - Mustererkennung KW - Frühdruck KW - pattern perception KW - early printed books Y1 - 2006 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-30429 ER - TY - THES A1 - Feineis, Markus T1 - Wortgenaue Annotation digitalisierter mittelalterlicher Handschriften T1 - One-to-one Annotation of Digitised Medieval Manuscripts N2 - No abstract available KW - Annotation KW - Handschrift KW - Digitalisierung Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-30448 ER -