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Use of colour for hand-filled form analysis and recognition
Colour information in form analysis is currently under utilised. As technology has advanced and computing costs have reduced, the processing of forms in colour has now become practicable. This paper describes a novel colour-based approach to the extraction of filled data from colour form images. Images are first quantised to reduce the colour complexity and data is extracted by examining the colour characteristics of the images. The improved performance of the proposed method has been verified by comparing the processing time, recognition rate, extraction precision and recall rate to that of an equivalent black and white system
Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image Matching
This paper presents a robotic pick-and-place system that is capable of
grasping and recognizing both known and novel objects in cluttered
environments. The key new feature of the system is that it handles a wide range
of object categories without needing any task-specific training data for novel
objects. To achieve this, it first uses a category-agnostic affordance
prediction algorithm to select and execute among four different grasping
primitive behaviors. It then recognizes picked objects with a cross-domain
image classification framework that matches observed images to product images.
Since product images are readily available for a wide range of objects (e.g.,
from the web), the system works out-of-the-box for novel objects without
requiring any additional training data. Exhaustive experimental results
demonstrate that our multi-affordance grasping achieves high success rates for
a wide variety of objects in clutter, and our recognition algorithm achieves
high accuracy for both known and novel grasped objects. The approach was part
of the MIT-Princeton Team system that took 1st place in the stowing task at the
2017 Amazon Robotics Challenge. All code, datasets, and pre-trained models are
available online at http://arc.cs.princeton.eduComment: Project webpage: http://arc.cs.princeton.edu Summary video:
https://youtu.be/6fG7zwGfIk
Verification of Authenticity of Stamps in Documents
KlasickĂĄ inkoustovĂĄ razĂtka, kterĂĄ se pouĆŸĂvajĂ k autorizaci dokumentĆŻ, se dnes dĂky rozĆĄĂĆenĂ modernĂch technologiĂ dajĂ relativnÄ snadno padÄlat metodou oskenovĂĄnĂ a vytiĆĄtÄnĂ. V rĂĄmci diplomovĂ© prĂĄce je vyvĂjen automatickĂœ nĂĄstroj pro ovÄĆenĂ pravosti razĂtek, kterĂœ najde vyuĆŸitĂ zejmĂ©na v prostĆedĂch, kde je nutnĂ© zpracovĂĄvat velkĂ© mnoĆŸstvĂ dokumentĆŻ. Procesu ovÄĆenĂ pravosti razĂtka musĂ pĆirozenÄ pĆedchĂĄzet jeho detekce v dokumentu - Ășloha zpracovĂĄnĂ obrazu, kterĂĄ zatĂm nemĂĄ pĆesvÄdÄivĂ© ĆeĆĄenĂ. V tĂ©to diplomovĂ© prĂĄci je navrĆŸena zcela novĂĄ metoda detekce a ovÄĆenĂ pravosti razĂtka v barevnĂœch obrazech dokumentĆŻ. Tato metoda zahrnuje plnou segmentaci strĂĄnky za ĂșÄelem urÄenĂ kandidĂĄtnĂch ĆeĆĄenĂ, dĂĄle extrakci pĆĂznakĆŻ a nĂĄslednou klasifikaci kandidĂĄtĆŻ za pomoci algoritmu podpĆŻrnĂœch vektorĆŻ (SVM). Evaluace ukĂĄzala, ĆŸe algoritmus umoĆŸĆuje rozliĆĄovat razĂtka od jinĂœch barevnĂœch objektĆŻ v dokumentu jako jsou napĆĂklad loga a barevnĂ© nĂĄpisy. KromÄ toho algoritmus dokĂĄĆŸe rozliĆĄit pravĂĄ razĂtka od kopiĂ.Classical ink stamps and seals used for authentication of a document content have become relatively easy to forge by the scan & print technique since the technology is available to general public. For environments where a huge volume of documents is processed, an automatic system for verification of authenticity of stamps is being developed in the scope of this master's thesis. The process of stamp authenticity verification naturally must be preceded by the phase of stamp detection and segmentation - a difficult task of Document Image Analysis (DIA). In this master's thesis, a novel method for detection and verification of stamps in color document images is proposed. It involves a full segmentation of the page to identify candidate solutions, extraction of features, and further classification of the candidates by means of support vector machines. The evaluation has shown that the algorithm is capable of differentiating stamps from other color objects in the document such as logos or text and also genuine stamps from copied ones.
Infrared face recognition: a comprehensive review of methodologies and databases
Automatic face recognition is an area with immense practical potential which
includes a wide range of commercial and law enforcement applications. Hence it
is unsurprising that it continues to be one of the most active research areas
of computer vision. Even after over three decades of intense research, the
state-of-the-art in face recognition continues to improve, benefitting from
advances in a range of different research fields such as image processing,
pattern recognition, computer graphics, and physiology. Systems based on
visible spectrum images, the most researched face recognition modality, have
reached a significant level of maturity with some practical success. However,
they continue to face challenges in the presence of illumination, pose and
expression changes, as well as facial disguises, all of which can significantly
decrease recognition accuracy. Amongst various approaches which have been
proposed in an attempt to overcome these limitations, the use of infrared (IR)
imaging has emerged as a particularly promising research direction. This paper
presents a comprehensive and timely review of the literature on this subject.
Our key contributions are: (i) a summary of the inherent properties of infrared
imaging which makes this modality promising in the context of face recognition,
(ii) a systematic review of the most influential approaches, with a focus on
emerging common trends as well as key differences between alternative
methodologies, (iii) a description of the main databases of infrared facial
images available to the researcher, and lastly (iv) a discussion of the most
promising avenues for future research.Comment: Pattern Recognition, 2014. arXiv admin note: substantial text overlap
with arXiv:1306.160
State of Alaska Election Security Project Phase 2 Report
A laskaâs election system is among the most secure in the country,
and it has a number of safeguards other states are now adopting. But
the technology Alaska uses to record and count votes could be improvedâ
and the stateâs huge size, limited road system, and scattered communities
also create special challenges for insuring the integrity of the vote.
In this second phase of an ongoing study of Alaskaâs election
security, we recommend ways of strengthening the systemânot only the
technology but also the election procedures. The lieutenant governor
and the Division of Elections asked the University of Alaska Anchorage to
do this evaluation, which began in September 2007.Lieutenant Governor Sean Parnell.
State of Alaska Division of Elections.List of Appendices / Glossary / Study Team / Acknowledgments / Introduction / Summary of Recommendations / Part 1 Defense in Depth / Part 2 Fortification of Systems / Part 3 Confidence in Outcomes / Conclusions / Proposed Statement of Work for Phase 3: Implementation / Reference
High Capacity Analog Channels for Smart Documents
Widely-used valuable hardcopy documents such as passports, visas, driving licenses, educational certificates, entrance-passes for entertainment events etc. are conventionally protected against counterfeiting and data tampering attacks by applying analog security technologies (e.g. KINEGRAMSÂź, holograms, micro-printing, UV/IR inks etc.). How-ever, easy access to high quality, low price modern desktop publishing technology has left most of these technologies ineffective, giving rise to high quality false documents. The higher price and restricted usage are other drawbacks of the analog document pro-tection techniques. Digital watermarking and high capacity storage media such as IC-chips, optical data stripes etc. are the modern technologies being used in new machine-readable identity verification documents to ensure contents integrity; however, these technologies are either expensive or do not satisfy the application needs and demand to look for more efficient document protection technologies.
In this research three different high capacity analog channels: high density data stripe (HD-DataStripe), data hiding in printed halftone images (watermarking), and super-posed constant background grayscale image (CBGI) are investigated for hidden com-munication along with their applications in smart documents. On way to develop high capacity analog channels, noise encountered from printing and scanning (PS) process is investigated with the objective to recover the digital information encoded at nearly maximum channel utilization. By utilizing noise behaviour, countermeasures against the noise are taken accordingly in data recovery process.
HD-DataStripe is a printed binary image similar to the conventional 2-D barcodes (e.g. PDF417), but it offers much higher data storage capacity and is intended for machine-readable identity verification documents. The capacity offered by the HD-DataStripe is sufficient to store high quality biometric characteristics rather than extracted templates, in addition to the conventional bearer related data contained in a smart ID-card. It also eliminates the need for central database system (except for backup record) and other ex-pensive storage media, currently being used. While developing novel data-reading tech-nique for HD-DataStripe, to count for the unavoidable geometrical distortions, registra-tion marks pattern is chosen in such a way so that it results in accurate sampling points (a necessary condition for reliable data recovery at higher data encoding-rate). For more sophisticated distortions caused by the physical dot gain effects (intersymbol interfer-ence), the countermeasures such as application of sampling theorem, adaptive binariza-tion and post-data processing, each one of these providing only a necessary condition for reliable data recovery, are given. Finally, combining the various filters correspond-ing to these countermeasures, a novel Data-Reading technique for HD-DataStripe is given. The novel data-reading technique results in superior performance than the exist-ing techniques, intended for data recovery from printed media.
In another scenario a small-size HD-DataStripe with maximum entropy is used as a copy detection pattern by utilizing information loss encountered at nearly maximum channel capacity. While considering the application of HD-DataStripe in hardcopy documents (contracts, official letters etc.), unlike existing work [Zha04], it allows one-to-one contents matching and does not depend on hash functions and OCR technology, constraints mainly imposed by the low data storage capacity offered by the existing analog media.
For printed halftone images carrying hidden information higher capacity is mainly attributed to data-reading technique for HD-DataStripe that allows data recovery at higher printing resolution, a key requirement for a high quality watermarking technique in spatial domain. Digital halftoning and data encoding techniques are the other factors that contribute to data hiding technique given in this research. While considering security aspects, the new technique allows contents integrity and authenticity verification in the present scenario in which certain amount of errors are unavoidable, restricting the usage of existing techniques given for digital contents.
Finally, a superposed constant background grayscale image, obtained by the repeated application of a specially designed small binary pattern, is used as channel for hidden communication and it allows up to 33 pages of A-4 size foreground text to be encoded in one CBGI. The higher capacity is contributed from data encoding symbols and data reading technique
Robust iris recognition under unconstrained settings
Tese de mestrado integrado. Bioengenharia. Faculdade de Engenharia. Universidade do Porto. 201
SVS-JOIN : efficient spatial visual similarity join for geo-multimedia
In the big data era, massive amount of multimedia data with geo-tags has been generated and collected by smart devices equipped with mobile communications module and position sensor module. This trend has put forward higher request on large-scale geo-multimedia retrieval. Spatial similarity join is one of the significant problems in the area of spatial database. Previous works focused on spatial textual document search problem, rather than geo-multimedia retrieval. In this paper, we investigate a novel geo-multimedia retrieval paradigm named spatial visual similarity join (SVS-JOIN for short), which aims to search similar geo-image pairs in both aspects of geo-location and visual content. Firstly, the definition of SVS-JOIN is proposed and then we present the geographical similarity and visual similarity measurement. Inspired by the approach for textual similarity join, we develop an algorithm named SVS-JOIN B by combining the PPJOIN algorithm and visual similarity. Besides, an extension of it named SVS-JOIN G is developed, which utilizes spatial grid strategy to improve the search efficiency. To further speed up the search, a novel approach called SVS-JOIN Q is carefully designed, in which a quadtree and a global inverted index are employed. Comprehensive experiments are conducted on two geo-image datasets and the results demonstrate that our solution can address the SVS-JOIN problem effectively and efficiently
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