Lecture

Programming Project: Image Recognition

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In course

ME-213: Programmation pour ingénieur

Mettre en pratique les bases de la programmation vues au semestre précédent. Développer un logiciel structuré. Méthode de debug d'un logiciel. Introduction à la programmation scientifique. Introduction à l'instrumentation virtuelle. ...

Description

This lecture covers the implementation of an image recognition program in LabVIEW, focusing on reading and validating parameters, recognizing digits, and storing pixel information. The instructor also explains the main steps of the project, including error handling and programming for engineers.

Instructor

Christophe Salzmann

Expertise Real-time Internet ServicesReal-time controlQuality of Service and Bandwidth adaptationLabVIEW Education PhD | Remote experimentation, Network 2005 – 2005 EPFL Directed by Denis Gillet MS. Degree | Computer Science 1999 – 1999 University of Florida Directed by Prof. H. Latchman Teaching & PhD Past EPFL PhD Students as codirector Damien Perritaz, Evgeny Bogdanov, Wissam Halimi Courses Control systems + TP ME

Official source

Related concepts (18)

Facial recognition system

A facial recognition system is a technology potentially capable of matching a human face from a or a video frame against a database of faces. Such a system is typically employed to authenticate users through ID verification services, and works by pinpointing and measuring facial features from a given image. Development began on similar systems in the 1960s, beginning as a form of computer application. Since their inception, facial recognition systems have seen wider uses in recent times on smartphones and in other forms of technology, such as robotics.

Optical character recognition

Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of s of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene photo (for example the text on signs and billboards in a landscape photo) or from subtitle text superimposed on an image (for example: from a television broadcast).

Computer vision

Computer vision tasks include methods for , , and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. Understanding in this context means the transformation of visual images (the input to the retina in the human analog) into descriptions of the world that make sense to thought processes and can elicit appropriate action.

Activity recognition

Activity recognition aims to recognize the actions and goals of one or more agents from a series of observations on the agents' actions and the environmental conditions. Since the 1980s, this research field has captured the attention of several computer science communities due to its strength in providing personalized support for many different applications and its connection to many different fields of study such as medicine, human-computer interaction, or sociology.

Pixel

In digital imaging, a pixel (abbreviated px), pel, or picture element is the smallest addressable element in a raster image, or the smallest addressable element in a dot matrix display device. In most digital display devices, pixels are the smallest element that can be manipulated through software. Each pixel is a sample of an original or synthetic image; more samples typically provide more accurate representations of the original. The intensity of each pixel is variable.

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