Low-Cost Assistive System for Deaf People Based on Artificial Vision

Artificial vision has wide-ranging applications in the food sector; it is easy to use, relatively low cost and allows to conduct rapid non-destructive analyses. The aim of this study was to use artificial vision techniques to control and model the coffee roasting process. Samples of Castillo variety coffee were used to construct the roasting curve, with captured images at different times. Physico-chemical determinations, such as colour, titratable acidity, pH, humidity and chlorogenic acids, and caffeine content, were investigated on the coffee beans. Data were processed by (i) Principal component analysis (PCA) to observe the aggrupation depending on the roasting time, and (ii) partial least squares (PLS) regression to correlate the values of the analytical determinations with the image information. The results allowed to construct robust regression models, where the colour coordinates (L*, a*), pH and titratable acidity presented excellent values in prediction (R2Pred 0.95, 0.91, 0.94 and 0.92). The proposed algorithms were capable to correlate the chemical composition of the beans at each roasting time with changes in the images, showing promising results in the modelling of the coffee roasting process.

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Augmented Reality Framework for the Socialization between Elderly People

Handbook of Research on ICTs for Human-Centered Healthcare and Social Care Services ◽

10.4018/978-1-4666-3986-7.ch023 ◽

2013 ◽

pp. 430-448 ◽

Cited By ~ 2

Author(s):

Luis Almeida ◽

Paulo Menezes ◽

Jorge Dias

Keyword(s):

Virtual Reality ◽

Augmented Reality ◽

Elderly People ◽

Low Cost ◽

Well Being ◽

Artificial Vision ◽

Spatial Audio ◽

Measurement Instruments ◽

Face To Face ◽

Mind And Body

The socialization between elderly people assumes a key role on their mind and body well-being while loneliness expects to be one of major problems of our increasing age society. This research aims to study and develop a framework to support elderly people socialization when they are confined to their homes for some reason. It can be also adequate for people following some neurological or physical rehabilitation treatment remotely or monitoring behaviors in order to prevent potential diseases. This work proposes a framework that supports the socialization through Augmented Reality (AR) based on telepresence. The aim is a low cost solution that enables users to communicate and interact remotely, experiencing the benefits of a face-to-face meeting. The authors explore computers graphics, spatial audio, and artificial vision to induce sensations of being physical in the presence of other people and exploit the potential activities that such frameworks enable. TV and phones are elderly common companion devices that should be complementarily used with emergent AR technologies to enhance and create the remote presence feeling, minimizing the loneliness. Inspired by Virtual Reality (VR) studies, one of the authors’ goals is to explore if VR presence measurement instruments are useful in the AR context by reviewing literature on the area.

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Low Cost, Wearable Door-Bell Notification system for Deaf People using Arduino

International Journal of Engineering Trends and Technology ◽

10.14445/22315381/ijett-v51p220 ◽

2017 ◽

Vol 51 (2) ◽

pp. 115-119

Author(s):

Shital P Thakkar ◽

◽

Aditya Kumar Jain

Keyword(s):

Low Cost ◽

Deaf People ◽

Notification System

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Artificial vision system for object classification in real time using Raspberry Pi and a Web camera

Revista de Tecnologías de la Información y Comunicaciones ◽

10.35429/jitc.2021.13.5.20.25 ◽

2021 ◽

pp. 20-25

Author(s):

Tomás Serrano-Ramírez ◽

Ninfa del Carmen Lozano-Rincón ◽

Arturo Mandujano-Nava ◽

Yosafat Jetsemaní Sámano-Flores

Keyword(s):

Embedded System ◽

Real Time ◽

Vision System ◽

Low Cost ◽

Artificial Vision ◽

Maintenance Cost ◽

Raspberry Pi ◽

Smart Cameras ◽

Suggested Technique ◽

Web Camera

Computer vision systems are an essential part in industrial automation tasks such as: identification, selection, measurement, defect detection and quality control in parts and components. There are smart cameras used to perform tasks, however, their high acquisition and maintenance cost is restrictive. In this work, a novel low-cost artificial vision system is proposed for classifying objects in real time, using the Raspberry Pi 3B + embedded system, a Web camera and the Open CV artificial vision library. The suggested technique comprises the training of a supervised classification system of the Haar Cascade type, with image banks of the object to be recognized, subsequently generating a predictive model which is put to the test with real-time detection, as well as the calculation for the prediction error. This seeks to build a powerful vision system, affordable and also developed using free software.

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Low-Cost System for Weld Tracking Based on Artificial Vision

IEEE Transactions on Industry Applications ◽

10.1109/tia.2011.2124432 ◽

2011 ◽

Vol 47 (3) ◽

pp. 1159-1167 ◽

Cited By ~ 23

Author(s):

Alberto Fernandez Villan ◽

Rodrigo Garcia Acevedo ◽

Eduardo Alvarez Alvarez ◽

Antonio Campos Lopez ◽

Daniel F. Garcia ◽

...

Keyword(s):

Low Cost ◽

Artificial Vision ◽

Cost System

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An automatic visual system for marble tile classification

Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture ◽

10.1243/095440502760272377 ◽

2002 ◽

Vol 216 (8) ◽

pp. 1095-1108 ◽

Cited By ~ 6

Author(s):

L Carrino ◽

W Polini ◽

S Turchetta

Keyword(s):

Visual System ◽

Low Cost ◽

International Market ◽

Artificial Vision ◽

Selection Line ◽

Quadratic Discriminant Analysis ◽

East Europe ◽

Ornamental Stone ◽

Multifactor Analysis ◽

Hardware And Software System

The international market of ornamental stone has seen the use of materials quarrying from East Europe, Africa, Asia and South America, characterized by a low cost of labour. This event has embittered the competition in this field. Hence, it becomes fundamental to produce machined products of high quality in a more efficient way. This work aims to design and fulfil a prototype to automatically classify the Royal Perlato tiles of Coreno. It is based on artificial vision. The implemented hardware visual system is cheap because it is made up of components readily available and is easily obtainable by small and medium ornamental stone businesses. The developed software algorithm is based on a multifactor analysis of variance and a quadratic discriminant analysis. The experimental results show that the developed hardware and software system permits all the tiles of Royal Perlato of Coreno to be classified properly. Moreover, the developed system not only improves the efficiency of the selection but also reduces the controversies between the manufacturer and buyer, making tile classification more selective and increasing the number of qualitative classes taken into consideration. Finally, it allows the duplication on the selection line without altering data dispersion.

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A Low Cost Artificial Vision System for Visually Impaired People

2009 Second International Conference on Computer and Electrical Engineering ◽

10.1109/iccee.2009.187 ◽

2009 ◽

Cited By ~ 3

Author(s):

Asim Iqbal ◽

Umar Farooq ◽

Hassan Mahmood ◽

Muhammad Usman Asad

Keyword(s):

Visually Impaired ◽

Vision System ◽

Low Cost ◽

Artificial Vision ◽

Visually Impaired People ◽

Impaired People

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An Application of Fish Detection Based on Eye Search with Artificial Vision and Artificial Neural Networks

Water ◽

10.3390/w12113013 ◽

2020 ◽

Vol 12 (11) ◽

pp. 3013

Author(s):

Ángel J. Rico-Díaz ◽

Juan R. Rabuñal ◽

Marcos Gestal ◽

Omar A. Mures ◽

Jerónimo Puertas

Keyword(s):

Low Cost ◽

Fish Farm ◽

Artificial Vision ◽

Stereo Image ◽

Disparity Map ◽

Image Recording ◽

Non Invasive ◽

Accuracy And Precision ◽

Feed Forward Network ◽

Invasive Method

A fish can be detected by means of artificial vision techniques, without human intervention or handling the fish. This work presents an application for detecting moving fish in water by artificial vision based on the detection of a fish′s eye in the image, using the Hough algorithm and a Feed-Forward network. In addition, this method of detection is combined with stereo image recording, creating a disparity map to estimate the size of the detected fish. The accuracy and precision of this approach has been tested in several assays with living fish. This technique is a non-invasive method working in real-time and it can be carried out with low cost. Furthermore, it could find application in aquariums, fish farm management and to count the number of fish which swim through a fishway. In a fish farm it is important to know how the size of the fish evolves in order to plan the feeding and when to be able to catch fish. Our methodology allows fish to be detected and their size and weight estimated as they move underwater, engaging in natural behavior.

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