scholarly journals Implementasi Pengolahan Citra Digital Sebagai Pengukur Nilai Resistor Pada Sistem Pemindai Resistor Berbasis Android

2015 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Satrio Firmansyah ◽  
Danang Lelono ◽  
Rade Sumiharto
Keyword(s):  
Image Processing ◽  
Light Intensity ◽  
Digital Image Processing ◽  
Digital Image ◽  
Color Space ◽  
Detection Distance ◽  
Hsv Color Space ◽  
Maximum Value ◽  
Actual Color ◽  
Color Value

AbstrakSalah satu gadget yang sering digunakan adalah telepon pintar berbasis Android. Android bersifat Open Source sehingga memungkinkan pengguna dan pengembang dalam mengoperasikan maupun membuat aplikasi berbasis Android. Ada berbagai macam permasalahan yang membutuhkan citra sebagai masukan atau input sistem dikarenakan keterbatasan manusia dalam hal kecepatan memproses suatu fungsi matematis maupun algoritma pendukung didalamnya, selain itu juga masalah waktu dan lain sebagainya. Salah satu sistem yang membutuhkan citra sebagai masukannya adalah penentuan nilai resistor berdasarkan gelang warna. Untuk melakukan seleksi warna digunakan metode segmentasi warna pemodelan warna HSV. Dengan menggunakan model warna HSV dapat menjadi model warna yg dapat digunakan sebuah sistem untuk menentukan nilai warna resistor, karena komponen nilai hue adalah representasi dari nilai warna yang sebenarnya. Hal ini didukung dengan saturation yang berfungsi sebagai tingkat kejenuhan suatu warna dan nilai value sebagai nilai kecerahan warna. Uji coba sistem dilakukan dengan pengujian pengaruh intensitas cahaya dan jarak pendeteksian antara kamera dan resistor.Hasil dari penelitian ini berupa sebuah implementasi pengolahan citra digital sebagai pengukur nilai resistor. Hasil terbaik dicapai dengan kondisi ruangan pada intensitas cahaya lampu antara 400 lux hingga 1200 lux dengan jarak pendeteksian antar kamera dan resistor yaitu maksimal 20 cm. Kata kunci— pengolahan citra digital, Android, resistor, HSV, intensitas cahaya, java AbstractOne of the gadget that is often used is Android smart phones. Android is an OpenSource, it could help user and developer to operate and develop Android Application. There are several problems that need image as an input system, it is caused by the humas’s ability in doing some mathematic functions or supported algorythm. To make the selection color used HSV color space. By using HSV color space allows a system to determine the color value resistor, because the hue value of the component is a representation of the actual color value. This is supported by the saturation level that serves as a color saturation and value as a brightness of color.The results of this research is an implementation of digital image processing as a measure of the value of the resistor. The system is tested by the influence of light intensity and the distance between the camera and resistor. The best results were achieved with the conditions of the room in light intensity between 400 lux to 1200 lux the detection distance between the camera and resistor is 20 cm of maximum value. Keywords—digital image processing, Android, resitor, HSV, light intensity, java

The Research of the Digital Image-Processing of Colorful Painting

2014 ◽  
Vol 926-930 ◽  
pp. 3709-3712
Author(s):  
Yun Zhan ◽  
Jie Lei
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Digital Images ◽  
Color Space ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Practical Application ◽  
Digital Image Processing Technique ◽  
Basic Concepts

The research of the digital image-processing of colorful painting is mainly to aim at the objective circumstances between the digital image and drawing flat vision distortion. This paper is based on the basic concepts of the digital image-processing technique. It expounds digital images advantage, collect, characteristics, recognition and the choice of the color space, the practical application of the digital image in the painting area in sequence. Through the study, we found computer has powerful ability to analyze management in the colorful painting field.

scholarly journals Shrimps clusterization by size using digital image processing with CCA and DBSCAN

2020 ◽  
Vol 8 (2) ◽  
pp. 106-112
Author(s):  
Adri Priadana ◽  
Aris Wahyu Murdiyanto
Keyword(s):  
Image Processing ◽  
Light Intensity ◽  
Digital Image Processing ◽  
Digital Image ◽  
Spatial Clustering ◽  
Digital Camera ◽  
Harvest Time ◽  
Connected Component ◽  
Average Accuracy

The quality of farmed shrimps has several criteria, one of which is shrimp size. The shrimp selection was carried out by the contractor at the harvest time by grouping the shrimp based on their size. This study aims to apply digital image processing for shrimp clustering based on size using the connected component analysis (CCA) and density-based spatial clustering of applications with noise (DBSCAN) methods. Shrimp group images were taken with a digital camera at a light intensity of 1200-3200 lux. The clustering results were compared with clustering from direct observation by two experts, each of which obtained an accuracy of 79.81 % and 72.99 % so that the average accuracy of the method was 76.4 %.

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.

Development of New Image Registration Techniques – A Research Framework

2018 ◽  
Vol 8 (3) ◽  
pp. 50
Author(s):  
Sindhu Madhuri G. ◽  
Indira Gandhi M P
Keyword(s):  
Image Processing ◽  
Image Registration ◽  
Digital Image Processing ◽  
Digital Image ◽  
Creative Thinking ◽  
Reference Image ◽  
Transformation Technique ◽  
Research Framework ◽  
Registration Process ◽  
Data Source

Image is a basic and fundamental data source for the digital image processing. This image data source is required to be processed into information or intelligence and further to knowledge levels where it is required to understand and migrate into knowledge economy systems. Image registration is one of such key and most important process already identified in the digital image processing domain. Image registration is a process of bringing the reference image and sensed image into a common co-ordinate system, and application of complex transformation techniques for necessary comparison of reference with sensed images obtained from different - views, times, spaces, etc., in order to extract the valuable information and intelligence embedded in them. Due to the complexity of overall image registration process, it is difficult to suggest a single transformation technique even for a specific application. In addition, it is highly impossible to suggest one single transformation technique for comparison of various sensed images with a reference image during the image registration process. This research gap calls for the development of new image registration techniques for the application of more than one transformation technique during the image registration process for the necessary comparisons with reference image & sensed images, those are obtained from the available heterogeneous sources or sensors, based on the requirement. In addition, it is a basic need to attempt for the measurement of effectiveness of the image registration process also. Therefore, a research framework is developed for image registration process and attempted for the measurement of its effectiveness also. This new research area is a novel idea, and is expected to emerge as a provision for the knowledge computations with creative thinking through the embedded intelligence extraction during the complex image registration process.

DAYA TARIK DAN DAYA DORONG PERKEMBANGAN WILAYAH TERHADAP PERSEBARAN PEMANFAATAN LAHAN KOTA SINJAI KABUPATEN SINJAI

2019 ◽  
Vol 3 ◽  
pp. 377
Author(s):  
Didiet Haryadi Hakim ◽  
Roland A. Barkey ◽  
Ria Wikantari
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Pull Factors ◽  
Push Factor

Bertambahnya penduduk akan selalu diikuti oleh bertambahnya bangunan-bangunan permukiman maupun bukan permukiman di wilayah Kota Kabupaten Sinjai sehingga mengakibatkan adanya persebaran pemanfaatan lahan yang tidak terarah. Penelitian ini bertujuan untuk (1) Menganalisis persebaran pemanfaatan lahan Perkotaan Sinjai (2) Mengidentifikasi faktor yang menarik dan mendorong terjadinya migrasi penduduk Perkotaan Sinjai dan (3) Mengusulkan arahan pemanfaatan lahan Perkotaan Sinjai. Metode yang digunakan dalam penelitian ini adalah deskriptif kuantitatif. Pengumpulan data dilakukan dengan metode analisis pembobotan sesuai dengan hasil kuisioner dan mengakses data dari instansi terkait. Data diolah menggunakan alat analisis pengelolaan citra digital (Digital Image Processing) yaitu teknik analisis (manipulasi dan interpretasi) data digital dengan bantuan komputer. Hasil penelitian menunjukkan kondisi perkembangan Kota Kabupaten Sinjai dipengaruhi oleh aspek perkembangan permukiman, perdagangan, pendidikan dan kesehatan, Faktor Pendorong (push factor) terjadinya urbanisasi di Kota Kabupaten Sinjai adalah keterbatasan lapangan kerja, rendahnya pendapatan di daerah asal, keamanan, sarana kesehatan yang tidak lengkap dan pelayanan pendidikan yang tidak sesuai harapan. Faktor penarik (pull factors) terjadinya urbanisasi adalah faktor ekonomi yaitu tingginya pendapatan apabila bekerja di Kota Kabupaten Sinjai, tersedianya sarana pendidikan dan sarana kesehatan yang lengkap, dan faktor aksesibilitas yaitu transportasi yang murah dan mudah, kemudian mengetahui arahan pemanfaatan lahan Kota Sinjai.

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