Pelly Bay 1939-1954
Franz Van de Velde photographic codex
Première édition
This book examines the first photo album to document life at the Kugaaruk mission, which was founded at Arviligjuar and named Mission St. Pierre et la Vierge des Pauvres in 1935. This collection of photos offers a look into an Inuit community during the late 1930s through to the early 1950s. Lire la suite
This book examines the first photo album to document life at the Kugaaruk mission, which was founded at Arviligjuar and named Mission St. Pierre et la Vierge des Pauvres in 1935 by Father Pierre Henry, a member of the Missionary Oblates of Mary Immaculate (OMI).
Father Franz Van de Velde arrived in Pelly Bay at the Kugaaruk mission on 23 April 1938 and spent the next 50 years of his life in the Canadian Arctic. During this time, he kept a detailed photographic record of Inuit life and the Catholic mission's activities. The photographs show not only the emergence the community of Kugaaruk but also a way of life, a spiritual universe, and a vast surrounding territory.
Located in Nunavut, a territory created in Canada in 1999, Kugaaruk currently has a population of about one thousand people who self-identify as Netsilik Inuit. This population was obviously much less numerous during Father Van de Velde’s time. Kugaaruk holds the record for the coldest windchill ever recorded in Canada: -92° C based on an air temperature of -51° C. Father Van de Velde’s photos demonstrate how Inuit managed life in such conditions.
Preserved in the Oblate Archives, Father Van de Velde’s album is not a complete record of life at the mission— some photos have been inexplicably removed, others are of low quality, but this collection of photos is a unique, insightful historical document. This volume offers a replica of the original album with original legends inserted by Father Van de Velde. The editors have supplemented Van de Velde’s photos with selected plates that deepen the anthropological relevance of the collection and bring certain details into focus. These images are accompanied by short texts that explain Inuit life during the mid-twentieth century. These texts were compiled from a range of sources: the report by Knud Rasmussen, who travelled through Netsilik country in the 1920s while leading the Fifth Thule Expedition; Father Van de Velde’s archives; publications by anthropologists who worked in the region; and original oral accounts from several knowledge-sharing workshops organized with the assistance of Nunavut Arctic College.
This collection of photos offers a look into an Inuit community during the late 1930s through to the early 1950s. The volume represents the way Father Van de Velde saw the community: his choices of what
and who to photograph, which images he put on the same plate, and the way he arranged the collection were conscious decisions that shaped this unique picture of the Kugaaruk community.
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Spécifications
- Éditeur
- Presses universitaires de Louvain
- Édité par
- Frédéric Laugrand, Emmanuel Luce,
- Langue
- anglais
- Catégorie (éditeur)
- Sciences économiques et sociales > Sciences politiques et sociales > Anthropologie
- BISAC Subject Heading
- SOC002010 SOCIAL SCIENCE / Anthropology / Cultural & Social > SOC021000 SOCIAL SCIENCE / Ethnic Studies / Native American Studies
- BIC subject category (UK)
- JHM Anthropology > JHMP Physical anthropology & ethnography > JHMC Social & cultural anthropology
- Code publique Onix
- 06 Professionnel et académique
- CLIL (Version 2013-2019 )
- 3111 Anthropologie
- Date de première publication du titre
- 03 juillet 2019
- Type d'ouvrage
- Monographie
Livre broché
- Date de publication
- 01 janvier 2005
- ISBN-13
- 978-2-93034-493-5
- Ampleur
- Nombre de pages de contenu principal : 108
- Code interne
- 72058
- Format
- 13,5 x 21 x 0,6 cm
- Poids
- 141 grammes
- Prix
- 10,90 €
- ONIX XML
- Version 2.1, Version 3
- Date de publication
- 01 janvier 2005
- ISBN-13
- 978-2-87463-537-3
- Ampleur
- Nombre de pages de contenu principal : 108
- Code interne
- 72058PDF
- Prix
- 5,50 €
- ONIX XML
- Version 2.1, Version 3
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Sommaire
Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . vii
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
Acknowledgement . . . . . . . . . . . . . . . . . . . . . xi
Table of Contents . . . . . . . . . . . . . . . . . . . . . . xiv
List of Acronyms . . . . . . . . . . . . . . . . . . . . . . xxv
1 Introduction 1
1.1 Current Document Analysis . . . . . . . . . . . . . 1
1.2 What is Natural Scene Text? . . . . . . . . . . . . 2
1.3 Numerous Applications . . . . . . . . . . . . . . . 5
1.4 Text Understanding System: Main Steps . . . . . . 7
1.5 Challenges and Overview of Problem Bounds . . . 9
1.6 Overall Structure . . . . . . . . . . . . . . . . . . . 10
2 Image Formation and Representation 13
2.1 Image Formation: Why do Colors Vary for the same Object? . . . . . . . . . . . . . . . . . . . . . 13
2.1.1 Light . . . . . . . . . . . . . . . . . . . . . . 13
2.1.2 Object . . . . . . . . . . . . . . . . . . . . . 14
2.1.3 Camera . . . . . . . . . . . . . . . . . . . . 17
2.2 Image Representation: Why do Different Color Spaces Exist? . . . . . . . . . . . . . . . . . . . . . 18
2.3 To Summarize... . . . . . . . . . . . . . . . . . . . 22
3 Background and Literature Survey of Text Understanding 23
3.1 State-of-the-Art of Text Extraction . . . . . . . . . 23
3.1.1 Thresholding-based methods . . . . . . . . 24
3.1.2 Grouping-based methods . . . . . . . . . . 27
3.1.3 Extensively used clustering methods in text extraction . . . . . . . . . . . . . . . . . . . 30
3.1.4 Challenges . . . . . . . . . . . . . . . . . . 34
3.2 Required Pre- and Post-Processing Steps for Efficient Text Understanding . . . . . . . . . . . . . . 34
3.2.1 Pre-processing steps of text extraction . . . 35
3.2.2 Post-processing steps of text extraction . . 37
3.2.3 Challenges . . . . . . . . . . . . . . . . . . 39
4 Text Understanding System 41
4.1 Text Understanding Chain . . . . . . . . . . . . . . 41
4.2 Material and Databases . . . . . . . . . . . . . . . 44
5 Resolution Enhancement 47
5.1 Resolution Enhancement for Still Images . . . . . . 48
5.2 Super-Resolution for Video Frames . . . . . . . . . 49
5.2.1 Context of super-resolution algorithms . . . 50
5.2.2 Color super-resolution text . . . . . . . . . 61
5.3 SURETEXT - Super-Resolution Text . . . . . . . 62
5.3.1 Motion estimation using the Taylor series . 62
5.3.2 Unsharp masking using the Teager filter . . 64
5.3.3 Outlier frame removal . . . . . . . . . . . . 66
5.3.4 Median denoising . . . . . . . . . . . . . . . 66
5.4 Experiments and Results . . . . . . . . . . . . . . . 67
5.4.1 Evaluation of SURETEXT . . . . . . . . . 67
5.4.2 Comparison with state-of-the-art SR algorithms . . . . . . . . . . . . . . . . . . . . . 71
5.4.3 Computation cost . . . . . . . . . . . . . . 72
5.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . 73
6 Text Extraction 75
6.1 Impact of Color Spaces and Clustering Algorithms 75
6.1.1 Is there a better color space for NS text extraction? . . . . . . . . . . . . . . . . . . . 75
6.1.2 Considerations on different clustering algorithms . . . . . . . . . . . . . . . . . . . . . 77
6.1.3 Evaluation of color representation with state-of-the-art clustering algorithms . . . . 79
6.2 Role of Metrics in K-means . . . . . . . . . . . . . 83
6.2.1 Definition of some metrics, either distances or similarities . . . . . . . . . . . . . . . . . 83
6.2.2 Noteworthy properties of angle-based similarities and complementarity with the Euclidean distance . . . . . . . . . . . . . . . . 86
6.2.3 Evaluation of several metrics . . . . . . . . 88
6.3 SMC - Selective Metric Clustering for Text Extraction . . . . . . . . . . . . . . . . . . . . . . . . . . 92
6.3.1 Color reduction and color inversion . . . . . 92
6.3.2 Utilization of a multi-hypothesis text extraction . . . . . . . . . . . . . . . . . . . . 94
6.3.3 Extraction-by-segmentation . . . . . . . . . 96
6.3.4 SMC evaluation and results . . . . . . . . . 98
6.4 Conclusion of the Selective Metric Clustering Technique . . . . . . . . . . . . . . . . . . . . . . . . . . 100
7 Unit-based Segmentation 103
7.1 Line and Word Segmentation . . . . . . . . . . . . 103
7.1.1 Line segmentation . . . . . . . . . . . . . . 104
7.1.2 Word segmentation . . . . . . . . . . . . . . 105
7.2 Character Segmentation using Log-Gabor Filters . 106
7.2.1 Is character segmentation still useful? . . . 106
7.2.2 Why are log-Gabor filters appropriate for NS character segmentation? . . . . . . . . . 109
7.2.3 Character segmentation-by-recognition . . . 112
7.2.4 Evaluation . . . . . . . . . . . . . . . . . . 118
7.3 Conclusion of the Log-Gabor-based Character Segmentation . . . . . . . . . . . . . . . . . . . . . . . 121
8 Considerations on NS Character Recognition and Correction 123
8.1 NS Character Recognition . . . . . . . . . . . . . . 123
8.1.1 What is done in NS character recognition? 123
8.1.2 Description of the exploited recognition system . . . . . . . . . . . . . . . . . . . . . . 125
8.1.3 Conclusion on considerations of character recognition . . . . . . . . . . . . . . . . . . 131
8.2 Recognition-by-Correction . . . . . . . . . . . . . . 131
8.2.1 Context of OCR correction . . . . . . . . . 131
8.2.2 Lexicon-based non-word error correction . . 134
8.2.3 Evaluation . . . . . . . . . . . . . . . . . . 137
8.2.4 Conclusion on recognition-by-correction . . 141
8.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . 142
9 Conclusion 143
9.1 Conclusions and Contributions . . . . . . . . . . . 143
9.2 Interesting Prolongations and Discussion . . . . . . 147
A Color Spaces Conversion 165
B Expectation-Maximization 173