Vector quantization (VQ) is a classical quantization technique from signal processing that allows the modeling of probability density functions by the distribution of prototype vectors. Developed in the early 1980s by Robert M. Gray, it was originally used for data compression. It works by dividing a large set of points (vectors) into groups having approximately the same number of points closest to them. Each group is represented by its centroid point, as in k-means and some other clustering algorithms. In simpler terms, vector quantization chooses a set of points to represent a larger set of points.
Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene photo or from subtitle text superimposed on an image.
Handwriting recognition (HWR), also known as handwritten text recognition (HTR), is the ability of a computer to receive and interpret intelligible handwritten input from sources such as paper documents, photographs, touch-screens and other devices. The image of the written text may be sensed "off line" from a piece of paper by optical scanning or intelligent word recognition. Alternatively, the movements of the pen tip may be sensed "on line", for example by a pen-based computer screen surface, a generally easier task as there are more clues available. A handwriting recognition system handles formatting, performs correct segmentation into characters, and finds the most possible words.
In time series analysis, dynamic time warping (DTW) is an algorithm for measuring similarity between two temporal sequences, which may vary in speed. For instance, similarities in walking could be detected using DTW, even if one person was walking faster than the other, or if there were accelerations and decelerations during the course of an observation. DTW has been applied to temporal sequences of video, audio, and graphics data — indeed, any data that can be turned into a one-dimensional sequence can be analyzed with DTW. A well-known application has been automatic speech recognition, to cope with different speaking speeds. Other applications include speaker recognition and online signature recognition. It can also be used in partial shape matching applications.
Document processing is a field of research and a set of production processes aimed at making an analog document digital. Document processing does not simply aim to photograph or scan a document to obtain a digital image, but also to make it digitally intelligible. This includes extracting the structure of the document or the layout and then the content, which can take the form of text or images. The process can involve traditional computer vision algorithms, convolutional neural networks or manual labor. The problems addressed are related to semantic segmentation, object detection, optical character recognition (OCR), handwritten text recognition (HTR) and, more broadly, transcription, whether automatic or not. The term can also include the phase of digitizing the document using a scanner and the phase of interpreting the document, for example using natural language processing (NLP) or image classification technologies. It is applied in many industrial and scientific fields for the optimization of administrative processes, mail processing and the digitization of analog archives and historical documents.
Crowd counting is known to be act of counting the total crowd present in a certain area. The people in a certain area are called a crowd. The most direct method is to actually count each person in the crowd. For example, turnstiles are often used to precisely count the number of people entering an event.
Keystroke dynamics, keystroke biometrics, typing dynamics, ortyping biometrics refer to the collection of biometric information generated by key-press-related events that occur when a user types on a keyboard. Use of patterns in key operation to identify operators predates modern computing, and has been proposed as an authentication alternative to passwords and PIN numbers.
Sammon mapping or Sammon projection is an algorithm that maps a high-dimensional space to a space of lower dimensionality by trying to preserve the structure of inter-point distances in high-dimensional space in the lower-dimension projection.
A chain code is a lossless compression based image segmentation method for binary images based upon tracing image contours. The basic principle of chain coding, like other contour codings, is to separately encode each connected component, or "blob", in the image.
A smudge attack is an information extraction attack that discerns the password input of a touchscreen device such as a smartphone or tablet computer from fingerprint smudges. A team of researchers at the University of Pennsylvania were the first to investigate this type of attack in 2010. An attack occurs when an unauthorized user is in possession or is nearby the device of interest. The attacker relies on detecting the oily smudges produced and left behind by the user's fingers to find the pattern or code needed to access the device and its contents. Simple cameras, lights, fingerprint powder, and image processing software can be used to capture the fingerprint deposits created when the user unlocks their device. Under proper lighting and camera settings, the finger smudges can be easily detected, and the heaviest smudges can be used to infer the most frequent input swipes or taps from the user.
Marcos Faundez-Zanuy is full professor and the dean at Escuela Universitaria Politécnica de Mataró. He has a PhD in telecommunication from UPC. He was the chair of the European COST action 277 "Non-linear Speech Processing", as well as the secretary of COST-2102 "Cross-Modal Analysis of Verbal and Non-verbal Communication".
Handwritten biometric recognition is the process of identifying the author of a given text from the handwriting style. Handwritten biometric recognition belongs to behavioural biometric systems because it is based on something that the user has learned to do.
Matti Kalevi Pietikäinen is a Finnish computer scientist. He is currently Professor (emer.) in the Center for Machine Vision and Signal Analysis, University of Oulu. His research interests are in texture-based computer vision, face analysis, affective computing, biometrics, and vision-based perceptual interfaces. He was Director of the Center for Machine Vision Research, and Scientific Director of Infotech Oulu.
Sayre's paradox is a dilemma encountered in the design of automated handwriting recognition systems. A standard statement of the paradox is that a cursively written word cannot be recognized without being segmented and cannot be segmented without being recognized. The paradox was first articulated in a 1973 publication by Kenneth M. Sayre, after whom it was named.
A biometric device is a security identification and authentication device. Such devices use automated methods of verifying or recognising the identity of a living person based on a physiological or behavioral characteristic. These characteristics include fingerprints, facial images, iris and voice recognition.
Ulisses M. Braga Neto is a Brazilian-American electrical engineer and is currently Professor of Electrical and Computer Engineering at Texas A&M University. His main research areas are statistical pattern recognition, machine learning, signal and image processing, and systems biology. He has worked extensively in the field of error estimation for pattern recognition and machine learning, having published with Edward R. Dougherty the first book dedicated to this topic. Braga-Neto has also published a classroom textbook on Pattern Recognition and Machine Learning. He has also made contributions to the field of Mathematical morphology in signal and image processing.
Indic OCR refers to the process of converting text images written in Indic scripts into e-text using Optical character recognition (OCR) techniques. Broadly, it can also refer to the OCR systems of Brahmic scripts for languages of South Asia and Southeast Asia, not just the scripts of the Indian subcontinent, which are all written in an abugida-based writing system.
Pattern Recognition is a single blind peer-reviewed academic journal published by Elsevier Science. It was first published in 1968 by Pergamon Press. The founding editor-in-chief was Robert Ledley, who was succeeded from 2009 until 2016 by Ching Suen of Concordia University. Since 2016 the current editor-in-chief is Edwin Hancock of the University of York. The journal publishes papers in the general area of pattern recognition, including applications in the areas of image processing, computer vision, handwriting recognition, biometrics and biomedical signal processing. The journal awards the Pattern Recognition Society Medal to the best paper published in the journal each year. In 2020, the journal had an impact factor of 7.196 and it currently has a Scopus CiteScore of 13.1. Google Scholar currently lists the journal as ranked 6th in the top 20 publications in Computer Vision and Pattern Recognition.
Land cover maps are tools that provide vital information about the Earth's land use and cover patterns. They aid policy development, urban planning, and forest and agricultural monitoring.
