Composite description based on color vector quantization and visual primary features for CBIR tasks

2021 ◽  
Author(s):  
M. Daud Abdullah Asif ◽  
Jing Wang ◽  
Yongsheng Gao ◽  
Jun Zhou
Keyword(s):  
Vector Quantization ◽  
Color Vector ◽  
Composite Description

New Hardware Architecture for Self-Organizing Map Used for Color Vector Quantization

2019 ◽  
Vol 29 (01) ◽  
pp. 2050002
Author(s):  
Khaled Ben Khalifa ◽  
Ahmed Ghazi Blaiech ◽  
Mehdi Abadi ◽  
Mohamed Hedi Bedoui
Keyword(s):  
Vector Quantization ◽  
Recent Literature ◽  
Network Architectures ◽  
Self Organizing Map ◽  
Description Language ◽  
Field Programmable ◽  
Color Vector ◽  
Hardware Description ◽  
Som Network ◽  
Self Organizing

In this paper, we present a new generic architectural approach of a Self-Organizing Map (SOM). The proposed architecture, called the Diagonal-SOM (D-SOM), is described as an Hardware–Description-Language as an intellectual property kernel with easily adjustable parameters.The D-SOM architecture is based on a generic formalism that exploits two levels of the nested parallelism of neurons and connections. This solution is therefore considered as a system based on the cooperation of a distributed set of independent computations. The organization and structure of these calculations process an oriented data flow in order to find a better treatment distribution between different neuroprocessors. To validate the D-SOM architecture, we evaluate the performance of several SOM network architectures after their integration on a Xilinx Virtex-7 Field Programmable Gate Array support. The proposed solution allows the easy adaptation of learning to a large number of SOM topologies without any considerable design effort. [Formula: see text] SOM hardware is validated through FPGA implementation, where temporal performance is almost twice as fast as that obtained in the recent literature. The suggested D-SOM architecture is also validated through simulation on variable-sized SOM networks applied to color vector quantization.

scholarly journals Impression Generation of Indonesian Cultural Paintings for Mobile Application with Culture Dependent Color-Impression Metric Creation Contents

2014 ◽  
Vol 2 (1) ◽  
Author(s):  
Devira Nanda Kuswhara ◽  
Ali Ridho Barakbah ◽  
Nur Rosyid Mubtadai ◽  
Yuliana Setiowati
Keyword(s):  
Vector Quantization ◽  
Mobile Application ◽  
Point Of View ◽  
Generation System ◽  
Common People ◽  
New Model ◽  
Cultural Computing ◽  
Image Dataset ◽  
Color Vector ◽  
Image Query

Painting is one of complex image reflecting observations and feelings of the artist to the environment. This condition extends the need of painting impression generation system since common people with lack of art experience would have difficulties to interpret the painting. From this point of view we presents a new model to provide representative impressions of paintings by providing a color-impression metric taken from public survey and implement it for mobile application. The new model provides analytical functions to generate the representative impression of the image query. The functions consist of two main section: (1) The cultural-dependent color-impression metric creation which consist of conducting survey, applying normalized 3D color vector quantization to image dataset, generating image-impression metric, and generating color- impression metric; and (2) Impression generation of image query which consist of applying normalized 3D color vector quantization to image query and measuring the similarity between image query andcolor-impression metric. To perform our proposed impression generation system, we examine our system with Indonesian cultural image dataset and 5 different mobile devices. Our proposed system performs main color impression precision result with average precision of more than 60%. Brightness intensity and zooming affects the retrieved impressions. Rotating captures of an image generate the same retrieved impressions. The system also performs average response time vary in range 41263 to 117434 milliseconds from all devices.Keywords: impression generation system, color based impression, cultural computing, mobile application.

scholarly journals Komputasi Budaya Untuk Pencarian Gambar Semantik Pada Lukisan Budaya Indonesia Dengan Deteksi Dan Informasi Aliran Lukisan

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ratri Cahyaning Winedhar
Keyword(s):  
Convex Hull ◽  
Vector Quantization ◽  
Nearest Neighbor ◽  
Connected Component ◽  
K Nearest Neighbor ◽  
Connected Component Labeling ◽  
Labeling Algorithm ◽  
Color Vector

Lukisan merupakan salah satu gambaran kompleks yang mencerminkan pengamatan dan perasaan seniman terhadap lingkungan. Kondisi ini memperluas kebutuhan akan sistem pendeteksi citra budaya karena masyarakat awam yang kurang memiliki pengalaman artistik akan sulit mendapatkan kesan lukisannya. Oleh karena itu, peneliti menekankan penerapan lukisan budaya Indonesia ke dalam aplikasi mobile. Sistem yang diusulkan telah diimplementasikan pada 239 lukisan budaya Indonesia yang terdiri dari lima kategori gaya lukisan. Kategorinya adalah abstraksionisme, naturalisme, ekspresionisme, realisme, dan romantisme. Sistem mengekstrak 3 fitur, yaitu fitur warna, bentuk, dan tekstur. Ekstraksi ciri warna menggunakan Histogram 3D Color Vector Quantization. Ekstraksi fitur bentuk menggunakan Connected Component Labeling Algorithm (CCL) dengan menghitung nilai area, diameter setara, luas, convex hull, soliditas, eksentrisitas, dan perimeter masing-masing objek. Ekstraksi fitur tekstur menggunakan Gabor Transformation dengan 40 kernel. Sedangkan untuk ekstraksi impresi dilakukan survey terhadap beberapa orang tentang impresi lukisan budaya Indonesia. Survei ini dilakukan terhadap responden yang memahami seni lukis seperti pelukis, pemerhati lukisan, dan orang-orang yang berkecimpung di dunia seni rupa. Untuk menunjukkan gaya lukisan peneliti menggunakan proses klasifikasi menggunakan K-Nearest Neighbor. Hasil eksperimen menunjukan fitur warna sebagai fitur terbaik dalam impression query

scholarly journals Sistem Pencarian Semantik Impresi dengan Mekanisme Pembobotan Kombinasi Fitur Warna dan Fitur Bentuk

2018 ◽  
Vol 3 (1) ◽  
pp. 41
Author(s):  
Desi Amirullah
Keyword(s):  
Vector Quantization ◽  
Hu Moments ◽  
Color Vector

Pada saat ini, informasi mengenai makna pada setiap warna dan bentuk motif dalam tenun Songket Melayu Riau sangat terbatas sehingga menyebabkan pengrajin songket kurang mengetahui informasi dan nilai-nilai budaya yang terkandung dalam setiap motif songket. Pengrajin songket diharuskan mengerti pada makna yang terkandung dalam setiap warna dan bentuk motif songket, agar tidak menimbulkan kesalahan dalam mengkombinasikan motif pada kain songket yang dibuat. Pada penelitian ini kami mengusulkan paradigma baru dalam sistem pencarian Impresi motif Songket secara semantik, yaitu menggunakan Kueri gambar yang mengkombinasikan fitur warna dan fitur bentuk dengan menggunakan mekanisme pembobotan fitur warna dan bentuk, hasil pencarian ini menampilkan hasil berupa impresi. Kami menggunakan gambar motif Songket Melayu Riau sebanyak 142 buah, yang mana pada setiap motif songket mengandung impresi yang sudah di ekstraksi sehingga mudah dimengerti oleh masyarakat umum. Gambar Dataset dan kueri di ekstraksi dengan menggunakan metode 3D-Color Vector Quantization (3D-CVQ) untuk ekstraksi fitur warna dan metode Hu Moments Invariant untuk ekstraksi fitur bentuk. Pada eksperimen dengan 3 model pembobotan yang kami lakukan, dapat disimpulkan skor tertinggi sistem pencarian impresi dengan kueri gambar bernilai 7.8 dari total nilai 10 dengan model pembobotan fitur warna 0.75 dan fitur bentuk 0.25

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