scholarly journals Modified KNN-LVQ for Stairs Down Detection Based on Digital Image

2021 ◽  
Vol 12 (3) ◽  
pp. 141
Author(s):  
Ahmad Wali Satria Bahari Johan ◽  
Sekar Widyasari Putri ◽  
Granita Hajar ◽  
Ardian Yusuf Wicaksono
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Hybrid Method ◽  
Visually Impaired ◽  
Blind People ◽  
Gray Level ◽  
Computational Speed ◽  
Occurrence Matrix ◽  
Computing Speed

Persons with visual impairments need a tool that can detect obstacles around them. The obstacles that exist can endanger their activities. The obstacle that is quite dangerous for the visually impaired is the stairs down. The stairs down can cause accidents for blind people if they are not aware of their existence. Therefore we need a system that can identify the presence of stairs down. This study uses digital image processing technology in recognizing the stairs down. Digital images are used as input objects which will be extracted using the Gray Level Co-occurrence Matrix method and then classified using the KNN-LVQ hybrid method. The proposed algorithm is tested to determine the accuracy and computational speed obtained. Hybrid KNN-LVQ gets an accuracy of 95%. While the average computing speed obtained is 0.07248 (s).

Histogram Equalization Based on Rough Set

2012 ◽  
Vol 182-183 ◽  
pp. 1844-1848
Author(s):  
Peng Yan ◽  
Wu Zhan ◽  
Ou Yang Min-Zi
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Set Theory ◽  
Rough Set ◽  
Digital Image ◽  
Rough Set Theory ◽  
Histogram Equalization ◽  
Experimental Simulation ◽  
Gray Level ◽  
Approximate Measurement

In digital image processing, classical histogram equalization produce the loss of image information the caused by gray level of the output image may be too much merged. This paper mainly based on the concepts of the set approximate, classification approximate measurement and importance in the rough set theory, divided the appropriate boundary of the set, proposed an improved histogram equalization method, thus effectively solved the problem, gave the experimental simulation confirmation.

scholarly journals IDENTIFIKASI IKAN KERAPU BERDSARKAN POLA KULIT DENGAN METODE GLCM DAN EUCLIDEAN DISTANCE

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Atthariq Atthariq ◽  
Mai Amini
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Euclidean Distance ◽  
Gray Level

Industri perikanan di Indonesia mengembangkan ikan kerapu yang pada umumnya digunakan untuk kepentingan ekspor. Oleh karena itu pengekspor perlu mengelompokkan ikan kerapu tersebut dalam jenis-jenis tertentu. Untuk melihat jenis - jenis ikan kerapu tersebut secara fisik mempunyai ciri pola kulit yang mampu dibedakan oleh penglihatan manusia tetapi membutuhkan waktu yang sangat lama. Dengan adanya teknologi Digital Image Processing, identifikasi pola kulit ikan kerapu dapat dikembangkan dan bermanfaat khususnya dibidang pengekspor.Penelitian ini bertujuan untuk menerapkan metode Gray Level Co-Occurence Matrix untuk menghasilkan nilai fitur pada pola kulit pada ikan kerapu. Perbedaan pola kulit ikan kerapu digunakan dengan cara mengidentifikasi pada tiap-tiap pola kulit ikan kerapu dengan menggunakan metode Euclidean Distance yang hasilnya menentukan jenis ikan kerapu melalui pola kulit ikan kerapu.Dalam penelitian ini diperoleh tingkat keakuratan sistem ini yaitu 84%.

scholarly journals DETEKSI KERUSAKAN DAN KELAYAKAN BAN MOBIL BERDASARKAN EKSTRAKSI TEKSTUR MENGGUNAKAN GRAY LEVEL COOCCURRENCE MATRIX DENGAN METODE JARINGAN SYARAF TIRUAN

2021 ◽  
Vol 7 (4) ◽  
pp. 27-32
Author(s):  
Nugroho Febriyanto ◽  
Cahya Rahmad ◽  
Candra Bella Vista
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Gray Level

Penyebab kecelakaan di Indonesia salah satunya adalah faktor dari kondisi kendaraan yang tidak baik salah satunya kondisi ban yang mengalami kerusakan. Jenis kerusakan ban mobil terdiri dari empat jenis yaitu ban mobil aus, ban mobil aus pada bagian tertentu, ban mobil retak atau terkena paku, ban mobil pecah atau robek. Faktor lainnya yaitu kurang kesadaran atau kelalaian dari pengguna mobil  untuk selalu memeriksa kondisi kendaraan terutama kondisi ban sebelum digunakan. Untuk mengatasi hal tersebut maka diusulkan untuk membuat sistem pendeteksi kerusakan dan kelayakan pada ban mobil berbasis Digital Image Processing (Pengolahan Citra Digital). Pada skripsi ini menggunakan citra ban mobil untuk didekteksi jenis kerusakan pada ban tersebut berdasarkan tekstur menggunakan Gray Level Cooccurrence Matrix. Backpropagation digunakan untuk mengklasifikasikan jenis kerusakan ban mobil dari nilai ekstraksi tekstur. Pada 100 kali pengujian menunjukkan tingkat akurasi metode Backpropagation adalah 80%. Faktor yang mempengaruhi tingkat akurasi yaitu proses pengambilan citra, kondisi ban mobil yang akan diambil citranya, nilai parameter yang digunakan untuk klasifikasi, dan perubahan nilai parameter yang tidak signifikan. Selain itu pengguna kendaraan dapat mengirimkan kondisi ban mereka melalui aplikasi android yang dibuat pada skripsi ini untuk diketahui jenis kerusakan dan tingkat kelayakan. Sehingga pengguna mobil dapat mengambil keputusan untuk mengganti ban mobil tersebut atau tidak.

Digital image processing. I. Evaluation of gray level correction methods in vitro .

1994 ◽  
Vol 5 (1) ◽  
pp. 37-47 ◽  
Author(s):  
I. Fourmousis ◽  
U. Brägger ◽  
W. Bürgin ◽  
M. Tonetti ◽  
N. P. Lang
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Gray Level

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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