Design of Delta Robot Using Image Processing for Product Sorting Process

2021 ◽  
Author(s):  
Tran Vi Do ◽  
Nguyen Quoc Nam ◽  
Dang Duc Vinh ◽  
Nguyen Quoc Viet ◽  
Pham Nguyen Dat ◽  
...  
Keyword(s):  
Image Processing ◽  
Sorting Process ◽  
Delta Robot

Study on Image Processing Algorithm for Condom Sorting

2014 ◽  
Vol 536-537 ◽  
pp. 153-156
Author(s):  
Ying Zhu ◽  
Jian Cun Zhao ◽  
Sen Song ◽  
Zhao Shan Liu
Keyword(s):  
Image Processing ◽  
Recognition Rate ◽  
Conveyor Belt ◽  
Image Processing Algorithm ◽  
Front Position ◽  
Sorting Process ◽  
Combined Algorithm ◽  
Ring Position ◽  
Detection Effect ◽  
Linear Shape

In a condom sorting process, we need to shoot the state image of condom through the camera and do the ellipse detection to determine the front position of condom on the conveyor belt, so developing the image processing algorithms which can detect the condom ring is necessary. The algorithm based on the Hough circle detection can obtain better detection effect for the most forms of the condom ring position, but it can not correctly detect the circle when the image shows linear shape; the algorithm based on the contrast of the ring detection get better effect on the ring in the image showing linear, while it has a low recognition rate in more folded case. We combined the two algorithms to use, proposed a combined algorithm which overcame the respective shortcomings of the two algorithms. Verified by experiment, the results of detection, recognition rate and the average processing time show the combined algorithms get the best comprehensive effect.

scholarly journals IoT Based Automatic Tyre Sorting System

2019 ◽  
Vol 8 (4) ◽  
pp. 10828-10832
Keyword(s):  
Image Processing ◽  
Manufacturing Industry ◽  
Research Work ◽  
Outer Core ◽  
Raspberry Pi ◽  
Process Time ◽  
Geometrical Parameters ◽  
Outer Diameter ◽  
Sorting Process ◽  
Sorting System

Tyre segregation is one of the indispensible processes in tyre manufacturing industry. In tyre manufacturing industry various size of tyres are examined at segregation unit at a time. Till today the tyre segregation process is done manually which increases the manpower and process time. Tyre sorting is the process of segregating the tyres from different sizes. The sorting process is based on the Geometrical parameter (Inner Diameter, Outer Diameter, Outer Core button Design) of the tyre. This research work is aimed to automate the sorting process of different tyres using Image processing and IOT. This pioneering work depicts a prototype of segregation system which includes the image processing segment to categorize the type of tyres which are fitted for various vehicles. The proposed system consist of Conveyor system, Raspberry pi -3 controller, tyre collecting bin, Servo motor and Image processing camera. This system camera monitors the incoming various tyres from the conveyor, based on the geometrical parameters of the tyres they are segregated and placed in the appropriate tyre collecting bin and the same information is shared to the database through IOT. The proposed model is observed to be very efficient with its counterpart.

scholarly journals METODE KLASIFIKASI MUTU GREENBEAN KOPI ARABIKA LANANG DAN BIASA MENGGUNAKAN K-NEAREST NEIGHBOR BERDASARKAN BENTUK

2020 ◽  
Vol 18 (2) ◽  
pp. 1
Author(s):  
Dedy Ikhsan ◽  
Ema Utami ◽  
Ferry Wahyu Wibowo
Keyword(s):  
Image Processing ◽  
Classification System ◽  
Nearest Neighbor ◽  
K Nearest Neighbor ◽  
Random Data ◽  
Arabica Coffee ◽  
Trial Process ◽  
Classification Feature ◽  
Quality Classification ◽  
Sorting Process

During this time, the Greenbean coffee sorting process is still done manually which still has many shortcomings. Manually, this result is classified in inappropriate and inconsistent classification results due to human negligence. Grading in the processing and marketing sectors is important. Inappropriate grading opposes farmers simply because Lanang and ordinary Arabica coffee are the same. Hence, we need a consistent classification system. This research uses image processing to recognize Greenbean Arabica coffee. K-NN (K-Nearest Neighbor) method is used for a quality classification. This research will classify Arabica Greenbean coffee into 4 quality classes, namely intact Lanang Arabica, broken Lanang Arabica, intact ordinary Arabica, and ordinary broken Arabica. The search of trial process shows that K-NN classification feature is able to recognize Arabica coffee Greenbean into 4 classes with an accuracy value of 63.5%, very good at recognizing 90% of regular Arabica intact and 97% of whole Arabica intact. However, it is still weak in recognizing broken coffee Greenbean based on its type. The area feature is better in recognizing Arabica coffee Greenbean based on 4 classes with an accuracy of 69.8%. This research obtains 120 datasets from 80 tested data trains and 40 tested random data.

Rancang Bangun Mesin Pemilah Biji Pinang

2016 ◽  
Vol 9 (2) ◽  
pp. 157-166
Author(s):  
Muhammad Nauval Fauzi ◽  
Mahaputra Mahaputra
Keyword(s):  
Image Processing ◽  
Computing Time ◽  
Computational Time ◽  
Human Hand ◽  
Betel Nut ◽  
Theoretical Frameworks ◽  
Sorting Machine ◽  
Sorting Process ◽  
High Level

The objective of this study is how to read the image using a camera, a program of computational image processing to determine the quality of betel nut. The betel nut sorting machine can help to reduce workload of employee where before this is done manually by human hand. Betel nut sorting process based on the color can be done using a machine that works automatically which can increase the result capacity with high level of accuracy and consistency. This study discusses approaches and theoretical frameworks as well as image processing, statistical analysis of color to create a prototype of betel nut sorting machine through several stages, both in image processing, mechanics, computing, interfacing and pneumatic. The results of this study found that the good or bad quality of betel nut can be distinguished  by chromasity analysis, good quality has higher value chromasity than the bad one with an accuracy of 94%, the maximum conveyor speed of 18 cm/sec at 20 fps camera working mode, assuming that there is one nut available on each 6 cm range, computational time on the working mode of 20 fps, the maximum tolerable time of 50 ms, so that when it is made for 6 channel, the computing time becomes large. ABSTRAKPada penelitian ini yang menjadi sasaran adalah bagaimana membaca citra menggunakan kamera, melakukan program komputasi pengolahan citra untuk menentukan kualitas biji pinang. Mesin pemilah biji pinang ini dapat mengurangi beban kerja yang selama ini pemilahan dilakukan secara manual dengan tangan manusia, proses pemilahan biji pinang berdasarkan warna dapat dilakukan menggunakan mesin yang bekerja secara otomatis yang dapat meningkatkan kapasitas hasilnya, tingkat keakurasian yang tinggi dan juga konsisten. Penelitian ini membahas tentang pendekatan dan kerangka teoritis serta image processing, statistik analisis warna biji pinang untuk membuat prototipe mesin pemilah biji pinang melalui beberapa tahapan, baik secara image processing, mekanik, komputasi, interfacing dan pneumatik. Hasil penelitian ini didapatkan bahwa biji pinang yang kualitas baik dan jelek dapat dibedakan melalui analisis chromasity, pinang yang kualitas baik memiliki nilai chromasity yang lebih tinggi dibandingkan pinang kualitas jelek dengan akurasi 94%, kecepatan konveyor maksimal 18cm/detik pada mode kerja kamera 20 fps, dengan asumsi bahwa tiap 6 cm ada 1 buah pinang  yang tersedia di tiap jalurnya, waktu komputasi pada mode kerja 20 fps, maksimal waktu yang ditolerir sebesar 50ms, sehingga ketika dibuat untuk 6 jalur, waktu komputasi menjadi besar. Kata kunci : Mesin pemilah, biji pinang, image processing, komputasi, analisis chromasity

scholarly journals Image Processing Technique for Fruit Grading

2019 ◽  
Vol 8 (6) ◽  
pp. 3894-3897 ◽  
Keyword(s):  
Image Processing ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Grading Systems ◽  
Automated Grading ◽  
Fruit Grading ◽  
Sorting Process ◽  
Quality Check ◽  
Agricultural Industries ◽  
Processing Techniques

Agriculture plays a major part in the economic growth of India . As there is high demand for quality fruits in the market fruit grading process is considered as very important. Fruit grading by a human may cause inefficient and it may also leads to some error. Another problem is labour intensive and to solve the above problems agricultural industries introduce many automated grading systems. In this paper a concept was introduced to get quality fruits by observing its color, measuring its size and weight. Due to cost and inaccurate process, sorting tons of quality fruits to produce food products made from fruits is an another problem that is faced by most of the agricultural industries. Here a sorting process is introduced where the image of the fruit is captured and analyzed using image processing techniques and the defected fruit is discarding by this process. The main aim of this paper is to do the quality check of the fruits within a short span of time.

Some comments about observations and image processing of comet 29P/Schwassmann-Wachmann 1

1999 ◽  
Vol 173 ◽  
pp. 243-248
Author(s):  
D. Kubáček ◽  
A. Galád ◽  
A. Pravda
Keyword(s):  
Image Processing ◽  
Large Scale ◽  
Harvard College ◽  
Oak Ridge ◽  
Large Scale Structures ◽  
Short Period Comet ◽  
Short Period ◽  
Scale Structures ◽  
Harvard College Observatory ◽  
Period Comet

AbstractUnusual short-period comet 29P/Schwassmann-Wachmann 1 inspired many observers to explain its unpredictable outbursts. In this paper large scale structures and features from the inner part of the coma in time periods around outbursts are studied. CCD images were taken at Whipple Observatory, Mt. Hopkins, in 1989 and at Astronomical Observatory, Modra, from 1995 to 1998. Photographic plates of the comet were taken at Harvard College Observatory, Oak Ridge, from 1974 to 1982. The latter were digitized at first to apply the same techniques of image processing for optimizing the visibility of features in the coma during outbursts. Outbursts and coma structures show various shapes.

Analysis of the 9th November 1990 flare

2000 ◽  
Vol 179 ◽  
pp. 229-232
Author(s):  
Anita Joshi ◽  
Wahab Uddin
Keyword(s):  
Image Processing ◽  
Two Dimensional ◽  
Temporal Behaviour ◽  
Contour Maps ◽  
Dimensional Measurements ◽  
Processing Software ◽  
Image Processing Software

AbstractIn this paper we present complete two-dimensional measurements of the observed brightness of the 9th November 1990Hαflare, using a PDS microdensitometer scanner and image processing software MIDAS. The resulting isophotal contour maps, were used to describe morphological-cum-temporal behaviour of the flare and also the kernels of the flare. Correlation of theHαflare with SXR and MW radiations were also studied.

The 'well-known' theory of electron image formation

1983 ◽  
Vol 41 ◽  
pp. 288-289
Author(s):  
M.A. O'Keefe ◽  
W.O. Saxton
Keyword(s):  
Image Processing ◽  
Image Formation ◽  
Source Profiles ◽  
Electron Image

A recent paper by Kirkland on nonlinear electron image processing, referring to a relatively new textbook, highlights the persistence in the literature of calculations based on incomplete and/or incorrect models of electron imageing, notwithstanding the various papers which have recently pointed out the correct forms of the appropriate equations. Since at least part of the problem can be traced to underlying assumptions about the illumination coherence conditions, we attempt to clarify both the assumptions and the corresponding equations in this paper, illustrating the effects of an incorrect theory by means of images calculated in different ways.The first point to be made clear concerning the illumination coherence conditions is that (except for very thin specimens) it is insufficient simply to know the source profiles present, i.e. the ranges of different directions and energies (focus levels) present in the source; we must also know in general whether the various illumination components are coherent or incoherent with respect to one another.

Recent Applications of High Resolution Electron Microscopy to Crystalline Arrays of Virus Particles

1978 ◽  
Vol 36 (3) ◽  
pp. 470-482 ◽  
Author(s):  
R.W. Horne
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Analytical Techniques ◽  
Staining Technique ◽  
High Resolution Electron Microscopy ◽  
Optical Diffraction ◽  
Full Potential ◽  
Virus Particles ◽  
Resolution Electron ◽  
Wide Range

The technique of surrounding virus particles with a neutralised electron dense stain was described at the Fourth International Congress on Electron Microscopy, Berlin 1958 (see Home & Brenner, 1960, p. 625). For many years the negative staining technique in one form or another, has been applied to a wide range of biological materials. However, the full potential of the method has only recently been explored following the development and applications of optical diffraction and computer image analytical techniques to electron micrographs (cf. De Hosier & Klug, 1968; Markham 1968; Crowther et al., 1970; Home & Markham, 1973; Klug & Berger, 1974; Crowther & Klug, 1975). These image processing procedures have allowed a more precise and quantitative approach to be made concerning the interpretation, measurement and reconstruction of repeating features in certain biological systems.

An Overview of Digital Image Processing and Recognition (Invited Paper)

1982 ◽  
Vol 40 ◽  
pp. 700-702
Author(s):  
R. C. Gonzalez
Keyword(s):  
Image Processing ◽  
New York ◽  
Digital Image Processing ◽  
Digital Image ◽  
Practical Implementation ◽  
Submarine Cable ◽  
Vigorous Growth ◽  
Digitized Pictures ◽  
Processing Techniques ◽  
And Storage

Interest in digital image processing techniques dates back to the early 1920's, when digitized pictures of world news events were first transmitted by submarine cable between New York and London. Applications of digital image processing concepts, however, did not become widespread until the middle 1960's, when third-generation digital computers began to offer the speed and storage capabilities required for practical implementation of image processing algorithms. Since then, this area has experienced vigorous growth, having been a subject of interdisciplinary research in fields ranging from engineering and computer science to biology, chemistry, and medicine.

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