scholarly journals Klasifikasi Rambu Lalu Lintas Menggunakan Ekstraksi Ciri Wavelet Dan Jarak Euclidean

2019 ◽  
Vol 3 (1) ◽  
pp. 26-35
Author(s):  
Vincentius Abdi Gunawan ◽  
Ignatia Imelda Fitriani ◽  
Leonardus Sandy Ade Putra
Keyword(s):  
Feature Extraction ◽  
Euclidean Distance ◽  
Daily Life ◽  
Human Mobility ◽  
Haar Wavelet ◽  
Surrounding Area ◽  
Traffic Signs ◽  
Road Users ◽  
Traffic Area ◽  
Very High

Driving is one of the human activities in which daily life is often done.  Driving can be done by land, air, and sea.  Human mobility in driving is very high on land routes using various means of transportation.  For the sake of smooth driving, roads are often equipped with traffic signs in each traffic area.  Traffic signs are a means for road users to provide information and guidance for motorists about the situation in the surrounding area.  The number of motorists who lack awareness of the knowledge of reading traffic signs is one of the biggest causes of accidents in Indonesia.  So that a system is needed that can help in recognizing traffic signs, especially prohibited signs.  The system designed using Haar Wavelet feature extraction and Euclidean distance as a classification.  From the data that has been tested, the level of recognition in reading traffic signs is prohibited by 92%.

scholarly journals IMPLEMENTASI METODE CHAIN CODE UNTUK PENGENALAN RAMBU LALU LINTAS

2016 ◽  
Vol 12 (1) ◽  
Author(s):  
Ryan Agustian ◽  
Nugroho Agus H. ◽  
Junius Karel
Keyword(s):  
Feature Extraction ◽  
Euclidean Distance ◽  
Extraction Process ◽  
Test Results ◽  
Traffic Sign ◽  
Distance Method ◽  
Traffic Signs ◽  
Chain Code ◽  
Image Objects

Traffic sign is needed to give information to users so they can be aware in roads. There are many types of traffic signs and each has many forms and different from each other so users sometimes have difficuty in recognizing traffic signs. In this research, the signs used are signs based on Peraturan Menteri Perhubungan Republik Indonesia Nomor PM 13 Tahun 2014. Modified Chain Code method was implemented for feature extraction process and Euclidean Distance method is used to calculating the similarity. Testing is done with 5 types of tests i.e. resize image, objects truncated, added a few objects to image, added many objects to image and noise spots. The test results showed the accuracy of the image of traffic signs to be recognized is 92.5%.

scholarly journals PENGENALAN CITRA RAMBU LALU LINTAS MENGGUNAKAN EKSTRAKSI FITUR MOMENWARNA DAN K-NEAREST NEIGHBOR

2019 ◽  
Vol 3 (1) ◽  
pp. 39
Author(s):  
Rusma Eko Fiddy Rizarta ◽  
Donny Avianto
Keyword(s):  
Feature Extraction ◽  
Nearest Neighbor ◽  
Histogram Equalization ◽  
Extraction Methods ◽  
Feature Representation ◽  
K Nearest Neighbor ◽  
Traffic Signs ◽  
Road Users ◽  
Road Sign ◽  
Spatial Moment

The traffic signs are signs with specific shape and symbols, letters, numbers, or words which have the aim to warn or inform the road users. However, there are many road users who are not aware of the meaning of each signs. In this research, we develop an application which can classify a road sign image into three classes, priority four-way crossroad, do-not-park sign, and follow-this-road sign. Initially, the system will do preprocessing step such as grays calling, histogram equalization, and input image segmentation. Next, the feature extraction step will be conducted, namely the spatial moment feature extraction, normalized centering, and color statistics. Lastly, the feature representation from both extraction methods will be used to classify the image using K-nearest neighbor. Experiment result shows that the combination of both feature extraction methods gives promising result. From 21 training images and 15 testing images, the system can recognize the traffic signs with 100% accuracy with K=3, 86.6% with K=5, and 86.6% with K=7. Rambu lalu lintas merupakan salah satu alat perlengkapan jalan dalam bentuk tertentu yang memuat lambang, huruf, angka, kalimat yang digunakan untuk memberikan perintah, larangan, peringatan dan petunjuk bagi pengguna jalan agar tertib berlalu lintas. Namun, banyak di antara pengguna jalan yang belum mengetahui arti dari setiap rambu lalu lintas yang terpasang.Pada penelitian ini, dibuatlah suatu aplikasi yang mampu melakukan klasifikasi citra rambu ke dalam 3 kelas yaitu: peringatan simpang empat prioritas, larangan parkir dan perintah memasuki jalur atau lajur yang ditunjuk. Mula-mula sistem akan melakukan prapemrosesan seperti seperti: grayscalling, histogram equalization, dan segmentasi pada citra input. Selanjutnya, tahap ekstraksi ciri akan dilakukan pada citra hasil pra-pemrosesan. Adapun metode ekstraksi ciri yang digunakan pada penelitian kali ini adalah ekstraksi fitur momen spasial dan pusat ternormalisai (momen) dan ekstraksi fitur statistika warna (warna). Terakhir, nilai fitur yang dihasilkan oleh kedua metode tersebut akan diklasifikasi mengguakan K-Nearest Neighbor. Hasil uji coba menunjukkan bahwa metode ekstraksi fitur gabungan momen-warna memberikan hasil yang menjanjikan. Dari 21 citra latih dan 15 citra uji yang digunakan, sistem mampu mengenali rambu dengan tepat 100% pada K=3 , 86,6% pada K=5, dan 86,6% pada K=7. 

NILAI BUDAYA DALAM CERITA RAKYAT MASYARAKAT ORANG ASLI TEMIAR GUA MUSANG, KELANTAN: SATU PENGAPLIKASIAN SASTERA WARISAN

2018 ◽  
Vol 6 (2) ◽  
pp. 101-120
Author(s):  
MOHD FAHMI BIN ISMAIL ◽  
MOHD FIRDAUS BIN CHE YAACOB
Keyword(s):  
Cultural Values ◽  
Indigenous People ◽  
Daily Life ◽  
Rapid Development ◽  
Empty Space ◽  
Indigenous Community ◽  
Orang Asli ◽  
Literature Research ◽  
Very High

Masyarakat Orang Asli Temiar merupakan komuniti orang yang telah lama wujud di negara kita.Kepelbagaian nilai budaya kehidupan masyarakat menjadi lambang jati diri dan kebanggaan masyarakatini. Oleh sebab itu, masyarakat Orang Asli Temiar ini sememangnya kaya dengan warisan ceritarakyat yang menjadi kebanggaan kepada masyarakat tersebut. Namun demikian, arus kepesatan,pembangunan dan kemajuan kemodenan menyebabkan khazanah cerita rakyat ini semakin dipinggirkanoleh masyarakat ini. Selain itu, mereka beranggapan bahawa medium lisan sebagai cerita mitos yangbercorak dongeng dan sekadar untuk berhibur semata-mata. Menerusi kajian ini, akan membincangkansatu objektif utama iaitu menganalisis nilai budaya dalam cerita rakyat masyarakat Orang Asli Temiar GuaMusang, Kelantan. Hal ini, dengan sendiri mewujudkan ruang ilmiah yang menuntut kepada pengkajianilmiah yang khusus. Sehubungan itu, pengkaji akan menggunakan kaedah kepustakaan dan kaedahkajian lapangan bagi memastikan kelancaran dalam menjalankan kajian tersebut. Selanjutnya, kajian iniakan menerapkan Teori Sastera Warisan yang dikemukakan oleh (A. Wahab Ali, 2005) sebagai gagasanuntuk memperkukuhkan dapatan kajian ini. Hasil dapatan kajian ini berhasil menemukan antara nilaibudaya yang selama ini menjadi landasan kepada ketamadunan masyarakat Orang Asli Temiar GuaMusang, Kelantan. Sementara itu, kemantapan elemen nilai budaya yang dihasilkan ini, dan diamalkandalam kehidupan seharian masyrakat ini, secara tidak lansung akan melahirkan kesan-kesan tersurat dantersirat kepada diri masyarakat komuniti ini. Kesimpulannya, cerita rakyat masyarakat Orang Asli Temiaradalah manifestasi kehidupan, adat kepercayaan dan lambang jati diri masyarakat ini.   Temiar indigenous people are a community are comunity of people living in the jugngle, marginalized andlangging in term of modernity country. There it can not be denied that this society is actually rich in diversecultures, fokstales and very high philosophy of thought. However, rapid development and modernity hasled to an increase in marginalized folklore Therefore open an empty space in scientifi c research whichrequired a specifi c research. This study aims to fi ll the empty space by examine the folktales of TemiarIndigenous community in Gua Musang, Kelantan. This study focused on three main objectives. First wasto show eff ect the folktales of Temiar Indigenous community in Gua Musang, Kelantan. Concomitantly, thisstudy used literature research and fi eld research. Furthermore, this study will apply the Sastera Warisantheory by Theory of Conceptual Keyword introduced by Mohamad Mokhtar Hassan in 2005 as the notionto strengthen this study. The realibility of cultural values hold by the Temiar Indigenous community and thepracticing of it in daily life infl uencing the Temiar Indigenous individually and collectively as community. Asconclusion, the folktales of Temiar Indigenous community can be said as manifestation of life, customsand beliefs, and sign of their identity.

scholarly journals Creative Practices of Contemporary Art in Daily Life of Jakarta. SOIJST Vol. 1 (1):1-16

2018 ◽  
Author(s):  
Muhammad Haris Mahyuddin
Keyword(s):  
Contemporary Art ◽  
First Principles ◽  
Energy Barrier ◽  
Daily Life ◽  
First Principles Calculation ◽  
Surface Material ◽  
Activation Energy Barrier ◽  
Reactor Technology ◽  
Frame Work ◽  
Very High

An interesting prospective pseudomorphic overlayer on bcc surface material as implemented in Pd pseudomorphic overlayer on V(110) surface has been introduced in the frame work of first-principles calculation. Adsorption and decomposition of H2S molecule were calculated on this overlayer structure. In comparison, we also calculated them on their bare V(110) and Pd(111) surfaces. It was found that Pseudomorphic overlayer surface structure weakened the adsorption energy of H2S, SH, S and H compared to its bare Pd(111) and V(110) surfaces. Furthermore, Pd/V(110) surface was found to have higher activation energy barrier for H2S and SH dissociation than its bare Pd(111) and V(110) do. Pd/V(110) surface is predicted to be a promising catalyst membrane used in gas-shift reactor technology because besides its advantage to absorb hydrogen with very high permeation coefficient, sulfur atom is predicted to be adsorbed in a limited amount.

scholarly journals Offline Signature Identification and Verification Based on Capsule Representations

2020 ◽  
Vol 20 (5) ◽  
pp. 60-67
Author(s):  
Dilara Gumusbas ◽  
Tulay Yildirim
Keyword(s):  
Feature Extraction ◽  
Daily Life ◽  
Extraction Methods ◽  
Signature Verification ◽  
Verification Task ◽  
Feature Representations ◽  
Automatic Feature Extraction ◽  
Offline Signature Verification ◽  
Orientation Information ◽  
Trained Network

AbstractOffline signature is one of the frequently used biometric traits in daily life and yet skilled forgeries are posing a great challenge for offline signature verification. To differentiate forgeries, a variety of research has been conducted on hand-crafted feature extraction methods until now. However, these methods have recently been set aside for automatic feature extraction methods such as Convolutional Neural Networks (CNN). Although these CNN-based algorithms often achieve satisfying results, they require either many samples in training or pre-trained network weights. Recently, Capsule Network has been proposed to model with fewer data by using the advantage of convolutional layers for automatic feature extraction. Moreover, feature representations are obtained as vectors instead of scalar activation values in CNN to keep orientation information. Since signature samples per user are limited and feature orientations in signature samples are highly informative, this paper first aims to evaluate the capability of Capsule Network for signature identification tasks on three benchmark databases. Capsule Network achieves 97 96, 94 89, 95 and 91% accuracy on CEDAR, GPDS-100 and MCYT databases for 64×64 and 32×32 resolutions, which are lower than usual, respectively. The second aim of the paper is to generalize the capability of Capsule Network concerning the verification task. Capsule Network achieves average 91, 86, and 89% accuracy on CEDAR, GPDS-100 and MCYT databases for 64×64 resolutions, respectively. Through this evaluation, the capability of Capsule Network is shown for offline verification and identification tasks.

scholarly journals Towards Sub-Pixel Automatic Geometric Corrections of Very-High Resolution Panchromatic Satellite Data of Urban Areas

2019 ◽  
Vol 11 (9) ◽  
pp. 1097 ◽  
Author(s):  
Aleš Marsetič ◽  
Peter Pehani
Keyword(s):  
Feature Extraction ◽  
High Resolution ◽  
Urban Areas ◽  
Satellite Images ◽  
Reference Data ◽  
Geometric Model ◽  
Control Point ◽  
Satellite Image ◽  
Extraction Algorithm ◽  
Very High

This paper presents an automatic procedure for the geometric corrections of very-high resolution (VHR) optical panchromatic satellite images. The procedure is composed of three steps: an automatic ground control point (GCP) extraction algorithm that matches the linear features that were extracted from the satellite image and reference data; a geometric model that applies a rational function model; and, the orthorectification procedure. Accurate geometric corrections can only be achieved if GCPs are employed to precisely correct the geometric biases of images. Due to the high resolution and the varied acquisition geometry of images, we propose a fast, segmentation based method for feature extraction. The research focuses on densely populated urban areas, which are very challenging in terms of feature extraction and matching. The proposed algorithm is capable of achieving results with a root mean square error of approximately one pixel or better, on a test set of 14 panchromatic Pléiades images. The procedure is robust and it performs well in urban areas, even for images with high off-nadir angles.

Traffic Sign Recognition Based on SIFT Features

2010 ◽  
Vol 121-122 ◽  
pp. 596-599 ◽  
Author(s):  
Ni An Cai ◽  
Wen Zhao Liang ◽  
Shao Qiu Xu ◽  
Fang Zhen Li
Keyword(s):  
Traditional Method ◽  
Euclidean Distance ◽  
Experimental Results ◽  
Traffic Sign Recognition ◽  
Recognition Method ◽  
Traffic Sign ◽  
Traffic Signs ◽  
Sign Recognition ◽  
Good Ability ◽  
Sift Features

A recognition method for traffic signs based on an SIFT features is proposed to solve the problems of distortion and occlusion. SIFT features are first extracted from traffic signs and matched by using the Euclidean distance. Then the recognition is implemented based on the similarity. Experimental results show that the proposed method, superior to traditional method, can excellently recognize traffic signs with the transformation of scale, rotation, and distortion and has a good ability of anti-noise and anti-occlusion.

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