scholarly journals The Implementation of Multilevel Colour Thresholding on a Prototype Coffee Machine

2020 ◽  
Vol 4 (2) ◽  
pp. 121
Author(s):  
Nova Resfita ◽  
Rahmadi Kurnia ◽  
Fitrilina Fitrilina
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Speech Recognition ◽  
Daily Life ◽  
Recognition System ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Speech Recognition System ◽  
Vast Number ◽  
Coffee Machine

The development of computer vision has expanded widely as there is a vast number of its applications in various aspects of daily life. One of its implementations is integrating the image processing technique on a prototype coffee machine based on the speech recognition system. This study aims to detect the requested coffee colour spoken by users which are black, middle and light. The sensor used in this research is a digital PC camera and the applied method is Multilevel Colour Thresholding. Of all experiments conducted, the image processing technique can work perfectly as the camera is able to identify the requested colour of the coffee solution. Furthermore, the system might be developed by improving the multilevel colour thresholding technique as well as advancing the hardware design in order to establish more robust coffee machine based on the requested colour.

scholarly journals Segmentation and Classification of Beatboxing Acoustic Voice Tract Variations in MRI through Image Processing Technique

2021 ◽  
Author(s):  
Anurag Sinha ◽  
Harsh soni
Keyword(s):  
Image Processing ◽  
Clustering Algorithms ◽  
Histogram Equalization ◽  
Recognition System ◽  
Processing Technique ◽  
Vital Role ◽  
Machine Learning Techniques ◽  
Image Processing Technique ◽  
Sound Recognition ◽  
Vocal Art

Human beatboxing is a vocal art making use of speech organs to produce vocal drum sounds and imitate musical instruments. Beatbox sound classification is a current challenge that can be used for automatic database annotation and music-information retrieval. In this study, a large-vocabulary humanbeatbox sound recognition system was developed with an adaptation of Kaldi toolbox, a widely-used tool for automatic speech recognition. The corpus consisted of eighty boxemes, which were recorded repeatedly by two beatboxers. The sounds were annotated and transcribed to the system by means of a beatbox specific morphographic writing system (Vocal Grammatics). The image processing techniques plays vital role on image Acquisition, image pre-processing, Clustering, Segmentation and Classification techniques with different kind of images such as Fruits, Medical, Vehicle and Digital text images etc. In this study the various images to remove unwanted noise and performs enhancement techniques such as contrast limited adaptive histogram equalization, Laplacian and Harr filtering, unsharp masking, sharpening, high boost filtering and color models then the Clustering algorithms are useful for data logically and extract pattern analysis, grouping, decision-making, and machine-learning techniques and Segment the regions using binary, K-means and OTSU segmentation algorithm. It Classifying the images with the help of SVM and K-Nearest Neighbour(KNN) Classifier to produce good results for those images.

scholarly journals Smart Leaf Recognition System

2020 ◽  
Vol 9 (5) ◽  
pp. 289-291
Keyword(s):  
Image Processing ◽  
Early Stage ◽  
Recognition System ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Plant Leaves ◽  
Plant Leaf ◽  
Automatic Technique

One of major issue nowadays is the agricultural productivity which is something our Nation’s economy highly depends. Technology based advancements may lead to detection of diseases in plants which are quite natural. Care should be taken in this area before it causes serious effects on plants which mainly affect the product quality, quantity or productivity. Early stage detection of diseases in plants through some automatic technique is beneficial as it reduces a huge work of monitoring in large acres of crops. When they appear on plant leaves, earlier detection helps us to increase the yield and productivity. This paper presents an algorithm for image processing technique which is used for automatic detection and classification of plant leaf diseases with the help of raspberry pi and sensors. This survey is about different diseases and its classification, techniques which are used for plant leaf disease detection and also its respective fertilizer sprayed on the leaves.

scholarly journals Harumanis mango leaf disease recognition system using image processing technique

2021 ◽  
Vol 23 (1) ◽  
pp. 378
Author(s):  
R. A. JM. Gining ◽  
S. S. M. Fauzi ◽  
N. M . Yusoff ◽  
T. R. Razak ◽  
M. H. Ismail ◽  
...  
Keyword(s):  
Image Processing ◽  
Recognition System ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Human Errors ◽  
Leaf Disease ◽  
Rgb Image

Current Harumanismango farming technique in Malaysia still mostlydepends on the farmers' own expertise to monitor the crops from the attack ofpests and insects. This approach is susceptible to human errors, and thosewho do not possess this skill may not be able to detect the disease at the righttime. As leaf diseases seriously affect the crop's growth and the quality of theyield, this study aims to develop a recognition system that detects thepresence of disease in the mango leaf using image processing technique.First, the image is acquired through a smartphone camera; once it has beenpre-processed, it is then segmented in which the RGB image is converted toan HSI image, then the features are extracted. Lastly, the classification ofdisease is done to determine thetype of leaf disease. The proposed systemeffectively detects and classify the disease with an accuracy of 68.89%. Thefindings of this project will contribute to farmers and society's benefit, andresearchers can use the approach to address similar issues in future works.

Image Processing Techniques to Analyse a 3D Model

2015 ◽  
Vol 787 ◽  
pp. 922-926
Author(s):  
Mirji Sairaj Gururaj ◽  
A Arockia Selvakumar
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Three Dimensional ◽  
Human Perception ◽  
Spur Gear ◽  
Recognition System ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Three Dimensional Model ◽  
Detection Techniques

The Image processing technique incorporates human perception and intelligence which makes this field more interesting to the research community. The edge detection process is the most important step in image recognition system. In this paper a simple three dimensional model is created by taking the best edge detected image followed by comparison with various edge detection techniques using Labview software. HereCatia model of spur gear isdrawn by observing and analysing best suited edge detected image in order to make the design more precise in edges and geometry and also to make object recognition simple and further scope is given to design a Catia model using dimensional parameters with the help of vision assistant tool.

A New Image Processing Technique for STEM

1974 ◽  
Vol 32 ◽  
pp. 432-433
Author(s):  
Yasushi Kokubo ◽  
Hirotami Koike ◽  
Teruo Someya
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Scanning Electron Microscopy ◽  
Elastic Scattering ◽  
Field Emission ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Energy Analyzer ◽  
Scanning Microscope ◽  
Scanning Electron

One of the advantages of scanning electron microscopy is the capability for processing the image contrast, i.e., the image processing technique. Crewe et al were the first to apply this technique to a field emission scanning microscope and show images of individual atoms. They obtained a contrast which depended exclusively on the atomic numbers of specimen elements (Zcontrast), by displaying the images treated with the intensity ratio of elastically scattered to inelastically scattered electrons. The elastic scattering electrons were extracted by a solid detector and inelastic scattering electrons by an energy analyzer. We noted, however, that there is a possibility of the same contrast being obtained only by using an annular-type solid detector consisting of multiple concentric detector elements.

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

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