scholarly journals A Novel Apple Size and Surface Quality Detection and Grading System

2019 ◽  
Vol 18 (3) ◽  
pp. 237-242
Author(s):  
Li Liu ◽  
Xin Qiao ◽  
Xindong Shi ◽  
Qunming Liu ◽  
Yinggang Shi
Author(s):  
Karim Emara ◽  
Aya El-Kady ◽  
Eman shaaban ◽  
Mohamed ElEliemy

Rekayasa ◽  
2017 ◽  
Vol 10 (2) ◽  
pp. 71
Author(s):  
Kunto Aji Wibisono ◽  
Achmad Fiqhi Ibadillah

<p>Madura merupakan salah satu daerah penghasil tembakau di Indonseia. Tembakau Madura  merupakan jenis komoditi perkebunan yang memiliki nilai ekonomi tinggi. Sebagian besar tembakau madura diserap oleh pabrik rokok sebagai bahan baku utama rokok maupun sebagai racikan atau campuran kretek. Secara umum tembakau Madura sendiri dibagi menjadi tiga bagian: tembakau gunung, tembakau tegal, dan tembakau sawah. Jenis tembakau gunung adalah yang paling diburu oleh pabrik rokok, meski produktivitasnya terbilang sangat rendah dibanding tembakau sawah. Terdapat banyak jenis  varietas tembakau gunung yang ditanam petani di Madura, namun  yang memiliki karakteristik khas adalah tembaku Prancak – 95. Hal ini disebabkan  <a href="http://global-news.co.id/2016/04/tembakau-varietas-prancak-95-madura-diam-diam-dikembangkan-tiongkok/">Aroma tembakau Prancak-95 Madura tidak bisa ditiru oleh</a> jenis varietas tembaku lain di Indonesia. Hal lain yang membedakan yaitu terjadi karena kontur atau struktur tanah Madura yang memang khas, yang merupakan kelebihan dari tembakau Madura.Pada penelitian ini didesain sebuah sistem gradding untuk mendeteksi kualitas tembakau Prancak – 95 madura. Deteksi kualitas daun tembakau ini didasarkan pada dua ekstraksi fitur yaitu tekstur dan aromatik. Berdasarkan kedua fitur tersebut nantinya akan diklasifikasikan dengan menggunakan standard kualifikasi SNI. Sehingga  level akurasi deteksi kualitas daun tembakau Madura menjadi lebih optimal</p><p class="Normal1"><em>Kata Kunci: </em><em>Image extraction, Sensor Gas, Tembakau Madura</em><em>.</em></p><p class="Normal1" align="center">Implementation of Feature Image Extraction on Quality Classification of Maduraness Tobacco<strong></strong></p><p class="Normal1"><strong>ABSTRACT</strong></p><p><em>Madura is one of the tobacco producing areas in Indonesian. Madura tobacco is a type of plantation commodity that has high economic value. Most tobacco Madura is absorbed by cigarette manufacturers as the main raw material of cigarettes as well as as a concoction or clove mixture. In general Madura tobacco itself is divided into three parts: mountain tobacco, tobacco tegal, and tobacco sawah. Types of mountain tobacco are the most hunted by cigarette manufacturers, although the productivity is very low compared to tobacco. There are many types of varieties of mountain tobacco grown by farmers in Madura, but which has a distinctive characteristic is the Prancak-95 tobacco. This is because the Prancak-95 Madura tobacco aroma cannot be imitated by other types of copious varieties in Indonesia. Another thing that distinguishes that occurs due to the contour or structure of Madura land that is typical, which is the advantage of Madura tobacco. In this study designed a grading system to detect the quality of Prancak tobacco - 95 madura. The tobacco leaf quality detection is based on two feature extractions, namely texture and aromatics. Based on these two features will be classified using SNI qualification standards. So that the accuracy level of Madura tobacco leaf quality detection becomes more optimal</em><em></em></p><em>Keywords: Image extraction, Gas Sensor, Maduraness Tobacco </em>


2015 ◽  
Vol 775 ◽  
pp. 214-218
Author(s):  
Yuan Lin ◽  
Hao Jiang ◽  
Huan Ran Lv ◽  
Xiu Wu Sui

By using analytical and finite element analysis method, this paper analyzes the various factors on the impact of EDM surface roughness, puts forward a new mirror machining method of changing the order of the processing conditions and increasing the momentum of the swinging electrode in the process of EDM. Puts a measuring method for the surface quality with white light interferometer characterized by non-contact, high precision and vertical resolution in nanometer. Experiments show that in the non-mixed powder fluid, without replacing the electrodes and the processed work-piece is 45 # steel, the surface roughness of work-piece is 0.02 micro-meter, which meets the requirements for precision of the electrical discharge mirror machining.


2008 ◽  
Author(s):  
Lihua Liu ◽  
Huiping Ma ◽  
Yunyan Ma ◽  
Pengsheng Li

2011 ◽  
Vol 301-303 ◽  
pp. 158-164 ◽  
Author(s):  
Chun Xiao Tang ◽  
En Bang Li ◽  
Chuan Zhen Zhao ◽  
Chao Li

This paper introduced an apple quality detection and specie identification system based on multi-spectral imaging. Under an international mixed light illumining, system can capture red, green and infrared images of apples at the same time. A software programmed based on Matlab 6.5.1 is used for image processing to complete the detection of quality and specie. According to processing results, the subtotals and classification are made into grading standards. These can be quickly and easily applied to the automation of agriculture fruit grading system. In the experiment, some most common apples including Fuji apple, Red delicious apples, Green apples, Gina Apple's were detected for quality and variety . Accuracy rate can be more than 90%.


2011 ◽  
Vol 314-316 ◽  
pp. 2394-2397
Author(s):  
Xin Ning ◽  
Li Pu Ning ◽  
Bin Feng Yang ◽  
Feng Tian ◽  
Xin Hua Mao

In this thesis, the digital figure of the defect of the casting elements is extracted by PCA. And a new method that simplifies the automatic quality detection is also brought forward. The author not only expounds the theory of PCA, the calculating method, the segmentation of digital figure and the feature extraction, but also analysis the real example to optimize the selecting of the preferences. This thesis is valuable in the real manufacture.


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