scholarly journals Adaptive Neuro-Fuzzy Inference System Based Grading of Basmati Rice Grains Using Image Processing Technique

2018 ◽  
Author(s):  
Dipankar Mandal
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Fuzzy Inference ◽  
Basmati Rice ◽  
Rice Grain ◽  
Milled Rice ◽  
Inference System ◽  
Rice Grains ◽  
Neuro Fuzzy

Grading of rice grains has gain attentions due its requirement of quality assessment during import or export. Rice grain quality depends on milling operation, where rice hull is removed with a huller system followed by whitening operation. In such process, adjustment of rollers, control, and operation is important in terms of quality of milled rice. Especially, the basmati rice needed more quality assurance as it is not parboiled rice and exported globally with a high product value. In this present work, the basic problem of quality assessment in rice industry is addressed with digital image processing based technique. Machine vision and digital image processing provide an alternative with the automated, nondestructive, cost-effective, and fast approach as compared with traditional method which is done manually by human inspectors. A model of quality grade testing and identification is built based on morphological features using digital image processing and knowledge based adaptive neuro-fuzzy inference system (ANFIS). The qualities of rice kernels are determined with the help of shape descriptors and geometric features using the sample images of milled rice. The adopted technique has been tested on a sufficient number of training images of basmati rice grain. The proposed method gives a promising result in an evaluation of rice quality with 100% classification accuracy for broken and whole grain. The milling efficiency is also assessed using the ratio between head rice and broken rice percentage and it is 77.27% for the test sample. The overall results of the adopted methodology are promising in terms of classification accuracy and efficiency.

scholarly journals PENGGUNAAN METODE ANFIS (ADAPTIVE NEURO FUZZY INFERENCE SYSTEM) PADA APLIKASI PREDIKSI USIA KERTAS

2015 ◽  
Vol 8 (2) ◽  
Author(s):  
Valeria Cynthia Dewi ◽  
Victor Amrizal ◽  
Fenty Eka Muzayyana Agustin
Keyword(s):  
Image Processing ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Inference System ◽  
Neuro Fuzzy

Kertas merupakan bahan yang tipis dan rata, yang dihasilkan dengan kompresi serat yang berasal dari pulp. Kertas merupakan  salah  satu  komponen  utama  dari  buku  dan  dokumen-dokumen.  Seiring  dengan  berkembangnya teknologi saat ini, bukan suatu hal yang tidak mungkin bagi seseorang untuk memalsukan dokumen dan merugikan beberapa pihak contohnya pemalsuan surat wasiat, time sheet records, dan rekam medis. Salah satu cara mengetahui keaslian kertas yaitu dengan mengetahui usia kertas tersebut menggunakan metode Penanggalan Karbon. Tetapi, dengan metode  konvensional masih memiliki  kelemahan  seperti membutuhkan  peralatan  yang  canggih,  biaya mahal, proses yang lama, dan askes yang terbatas. Untuk mengetahui usia kertas juga bisa diketahui dengan melihat perubahan warna pada kertas. Untuk memberikan solusi pada permasalahan yang ada, penulis membuat aplikasi yang dapat mengidentifikasi kisaran usia kertas dengan proses yang lebih cepat, biaya lebih murah, dan tidak harus dilakukan oleh pegawai laboratorium. Aplikasi bernama Aplikasi Prediksi Usia Kertas yang dibuat berbasis desktop menggunakan  bahasa  pemrograman  MATLAB.  Terdapat  dua  proses  yaitu  pembacaan  citra  dengan  Image Processing dengan cara mengambil nilai rata-rata CMYK dari 60 data latih dan proses pencocokan dengan metode ANFIS Sugeno  (TSK)  fungsi keanggotaan Gaussian. Penelitian didahulukan dengan wawancara, observasi, dan studi  literatur. Metode  pengembangan  aplikasi menggunakan  prototype.  Hasil  pengujian menunjukkan  tingkat keberhasilan aplikasi dalam mengidentifikasi 60 data latih sebesar 100% dan terhadap 40 data yang belum dilatih sebesar 42,5%.Kata Kunci: Usia Kertas, Penanggalan Karbon, ANFIS, Image Processing, CMYK

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.

A method to measure pores and fissures in geologic materials under S.E.M. by digital image processing

1978 ◽  
Vol 36 (1) ◽  
pp. 212-213
Author(s):  
L. Montoto ◽  
M. Montoto ◽  
A. Bel-Lan
Keyword(s):  
Image Processing ◽  
Optical Microscopy ◽  
Digital Image Processing ◽  
Digital Image ◽  
Digital Processing ◽  
Free Surfaces ◽  
Geologic Materials ◽  
Automatic Information ◽  
Detector Output ◽  
Rock Specimens

INTRODUCTION.- The physical properties of rock masses are greatly influenced by their internal discontinuities, like pores and fissures. So, these need to be measured as a basis for interpretation. To avoid the basic difficulties of measurement under optical microscopy and analogic image systems, the authors use S.E.M. and multiband digital image processing. In S.E.M., analog signal processing has been used to further image enhancement (1), but automatic information extraction can be achieved by simple digital processing of S.E.M. images (2). The use of multiband image would overcome difficulties such as artifacts introduced by the relative positions of sample and detector or the typicals encountered in optical microscopy.DIGITAL IMAGE PROCESSING.- The studied rock specimens were in the form of flat deformation-free surfaces observed under a Phillips SEM model 500. The SEM detector output signal was recorded in picture form in b&w negatives and digitized using a Perkin Elmer 1010 MP flat microdensitometer.

Digital image processing methods applied to the study of annealing time on semiconductor-metal eutectic composites

1988 ◽  
Vol 46 ◽  
pp. 848-849
Author(s):  
J. Hefter
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Electronic Device ◽  
Processing System ◽  
Average Diameter ◽  
Eutectic Solidification ◽  
Metal Silicide ◽  
The Matrix ◽  
Microscopic Studies

Semiconductor-metal composites, formed by the eutectic solidification of silicon and a metal silicide have been under investigation for some time for a number of electronic device applications. This composite system is comprised of a silicon matrix containing extended metal-silicide rod-shaped structures aligned in parallel throughout the material. The average diameter of such a rod in a typical system is about 1 μm. Thus, characterization of the rod morphology by electron microscope methods is necessitated.The types of morphometric information that may be obtained from such microscopic studies coupled with image processing are (i) the area fraction of rods in the matrix, (ii) the average rod diameter, (iii) an average circularity (roundness), and (iv) the number density (Nd;rods/cm2). To acquire electron images of these materials, a digital image processing system (Tracor Northern 5500/5600) attached to a JEOL JXA-840 analytical SEM has been used.

Complementary Z-Contrast Imaging and Digital Image Processing

1985 ◽  
Vol 43 ◽  
pp. 304-305
Author(s):  
K. N. Colonna ◽  
G. Oliphant
Keyword(s):  
Image Processing ◽  
Heavy Metal ◽  
Digital Image Processing ◽  
Digital Image ◽  
Biological Tissue ◽  
Biological Imaging ◽  
Tissue Preparation ◽  
Contrast Imaging ◽  
Imaging Tool ◽  
Z Contrast

Harmonious use of Z-contrast imaging and digital image processing as an analytical imaging tool was developed and demonstrated in studying the elemental constitution of human and maturing rabbit spermatozoa. Due to its analog origin (Fig. 1), the Z-contrast image offers information unique to the science of biological imaging. Despite the information and distinct advantages it offers, the potential of Z-contrast imaging is extremely limited without the application of techniques of digital image processing. For the first time in biological imaging, this study demonstrates the tremendous potential involved in the complementary use of Z-contrast imaging and digital image processing.Imaging in the Z-contrast mode is powerful for three distinct reasons, the first of which involves tissue preparation. It affords biologists the opportunity to visualize biological tissue without the use of heavy metal fixatives and stains. For years biologists have used heavy metal components to compensate for the limited electron scattering properties of biological tissue.

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