Skip to main content

What is Computer Vision and Machine Vision

 Computer vision describes the ability of computers or subsystems to identify

objects, scenes and activities in images. To this end, technologies are used

with the help of which the complex image analysis tasks are divided among

as small sub-tasks as possible and then computed. These techniques are

applied to recognise individual edges, lines and textures of objects in one.

Classification, machine learning and other processes, for example, are used

to determine whether the features identified in an image probably represent

an object already known to the system.



Computer vision has multifaceted applications, among them the anal-

ysis of medical imaging to improve prognoses, diagnoses and treatment

of diseases or facial recognition on Facebook, which ensures that users are

automatically recognised by algorithms and are suggested for tags. Such sys-

tems are already used for security and surveillance purposes for the identi-

fication of suspects. In addition, e-commerce companies such as Amazon

are working on systems with which specific products can be identified on

images and subsequently be purchased directly online. Whilst researchers in

the field of computer vision are working on the aim of being able to utilise

systems independent of the environment, with machine vision, sensors are

used with the help of which relevant information can be captured within

restricted environments. This discipline is technically mature to the extent

that it is no longer part of ongoing informatics research, but part of sys-

tem technology today. At the same time, it is less a matter of recognising

the meaning or content of an image but of deriving information relevant for

action.


Comments

Popular posts from this blog

Customer Engagement with Chatbots and Collaboration Bots: Methods, Chances and Risks of the Use of Bots in Service and Marketing

 Relevance and Potential of Bots for Customer  Obtaining information, flight check-ins or keeping a diary of one’s own diet—all of this is possible in dialogue today. Customers can ask questions via Messenger or WhatsApp or initiate processes. This service is comfortable for the customer, available at all times via mobile and promises fast answers or smooth problem-solving. A meanwhile strongly increasing number of companies is already relying on this means of contact and the figures on chat usage speak in favour of this means supplementing or even replacing many apps and web offers in the future. The reasons for this are manifold. Figures of the online magazine Business Insider 1 reveal a clear develop- ment away from the public post to the use of private messaging services such as Facebook Messenger or WhatsApp. Facebook meanwhile has a user base of around 1.7 billion people worldwide; 1.1 billion people use WhatsApp, and Twitter can nevertheless still record 310 million us...

Robot Journalism Is Becoming Creative

 Algorithms are able to automatically search the Web for information, pool it and create a readable piece of writing. In addition, data-based reports in the area of sport, the weather or finances are already frequently created automat- ically today. Recently, for example, merely a few minutes after Apple had announced their latest quarterly figures, there was a report by the news agency Associated Press (AP): “Apple tops Street 1Q forecasts”. The financial report deals solely with the mere financial figures, without any human assistance whatsoever. Yet, AP was able to publish their report entirely via AI in line with the AP guidelines. For this purpose, AP launched their corresponding platform Wordsmith at the beginning of 2016, which automatically creates more than 3000 of such financial reports every quarter, and which are pub- lished fast and accurately. It is no longer that easy to distinguish between whether an algorithm or a human has written a text. Another exception of rece...

A Bluffer’s Guide to AI, Algorithmics and Big Data

 Big Data—More Than “Big” A few years ago, the keyword big data resounded throughout the land. What is meant is the emergence and the analysis of huge amounts of data that is generated by the spreading of the Internet, social media, the increasing number of built-in sensors and the Internet of Things, etc. The phenomenon of large amounts of data is not new. Customer and credit card sensors at the point of sale, product identification via barcodes or RFID as well as the GPS positioning system have been producing large amounts of data for a long time. Likewise, the analysis of unstructured data, in the shape of business reports, e-mails, web form free texts or customer surveys, for example, is frequently part of internal analyses. Yet, what is new about the amounts of data falling under the term “big data” that has attracted so much attention recently? Of course, the amount of data avail- able through the Internet of Things (Industry 4.0), through mobile devices and social media has ...