Real Time Face Recognition Based on Face Descriptor and Its Application

This paper presents a real time face recognition based on face descriptor and its application for door locking. The face descriptor is represented by both local and global information. The local information, which is the dominant frequency content of sub-face, is extracted by zoned discrete cosine transforms (DCT). While the global information, which also is the dominant frequency content and shape information of the whole face, is extracted by DCT and by Hu-moment. Therefore, face descriptor has rich information about a face image which tends to provide good performance for real time face recognition. To decrease the dimensional size of face descriptor, the predictive linear discriminant analysis (PDLDA) is employed and the face classification is done by kNN. The experimental results show that the proposed real time face recognition provides good performances which indicated by 98.30%, 21.99%, and 1.8% of accuracy, FPR, and FNR respectively. In addition, it also needs short computational time (1 second)

Analisis Penggunaan Sensor Kamera 3 Dimensi Kinect sebagai Media Pembelajaran Perkuliahan berbasis Student Centered Learning

Saat ini, kegiatan belajar mengajar di berbagai universitas di Indonesia umumnya dilakukan menggunakan laptop yang terhubung ke sebuah proyektor. Di dalam proses pengajaran, dosen cenderung menggunakan laptop di ruang kelas, menghubungkan tampilan layar laptop ke sebuah proyektor, kemudian menggunakan wireless pointer sebagai pengendali slide presentasi. Pendekatan semacam ini sayangnya tergolong kurang efektif di dalam perkuliahan berbasis Student Centered Learning (SCL). Di dalam SCL, mahasiswa merupakan pusat kegiatan perkuliahan, dimana keterlibatan dan interaksi mahasiswa di dalam proses penyampaian materi merupakan hal terpenting guna meningkatkan animo dan pemahaman mahasiswa mempelajari suatu topik. Penggunaan teknologi perkuliahan konvensional seperti laptop dan wireless pointer cenderung membuat perkuliahan menjadi 1 arah karena interaksi mahasiswa kurang dapat tersalurkan. Di dalam penelitian ini, dilakukan analisis dampak penggunaan teknologi informasi sensor kamera 3 dimensi Kinect sebagai media pembelajaran dalam suatu sistem Smart Classroom. Kinect merupakan sensor yang dapat menangkap gerakan tangan seseorang kemudian menginterpretasikan gerakan tersebut sebagai suatu perintah komputasi berdasarkan algoritma pemrograman tertentu. Berdasarkan hasil penelitian, penggunaan Kinect terbukti dapat meningkatkan efektivitas pembelajaran SCL dan antusiasme belajar mahasiswa karena mahasiswa dapat berinteraksi di dalam suatu materi perkuliahan secara lebih alami menggunakan gerakan tangan

Fast pornographic image recognition using compact holistic features and multi-layer neural network

The paper presents an alternative fast pornographic image recognition using compact holistic features and multi-layer neural network (MNN). The compact holistic features of pornographic images, which are invariant features against pose and scale, is extracted by shape and frequency analysis on pornographic images under skin region of interests (ROIs). The main objective of this work is to design pornographic recognition scheme which not only can improve performances of existing methods (i.e., methods based on skin probability, scale invariant feature transform, eigenporn, and Multilayer-Perceptron and Neuro-Fuzzy (MP-NF)) but also can works fast for recognition. The experimental outcome display that our proposed system can improve 0.3% of accuracy and reduce 6.60% the false negative rate (FNR) of the best existing method (skin probability and eigenporn on YCbCr, SEP), respectively. Additionally, our proposed method also provides almost similar robust performances to the MP-NF on large size dataset. However, our proposed method needs short recognition time by about 0.021 seconds per image for both tested datasets

Image Retrieval using Modified Multi Texton and Rotation Invariant Local Binary Pattern

Image retrieval is a standard method used to search a digital image in large image databases. One of the most critical things in image retrieval is the feature extraction process. Several techniques can be used in the image feature extraction process, one of which is Multi Texton Histogram (MTH). MTH is usually carried out with two main processes, namely color quantization, and texture orientation. Improvement of MTH method performance can be made by adding texton. In our experiment, we test the method by using rotated images. In this paper, we develop the use of an invariant method for rotation, namely the Local Binary Pattern Rotation Invariant (LBPROT) method to improve image retrieval precision. The results of combining these two methods produce features of each image. The features produced by each image are compared using a distance matrix. A query image that has the smallest distance matrix value is an image that has the same class as the compared database image. Based on our experiments on typical images, the use of Modified MTH and LBPROT can improve image retrieval performance by increasing the percentage of precision and recall by 3.63% and 0.62%. However, The Modified MTH is better when compared to the merging of the Modified MTH and LBPROT on 45 °, 135 °, 225 °, and 315 ° angle rotations with precision values by 24% -27%. Meanwhile, our testing result using rotated images, the combination of Modified MTH and LBPROT produces an increase in precision at angles rotation of 90 °, 180 °, and 270 ° by 2% -3%

Low-Cost Camera-Based Smart Surveillance System for Detecting, Recognizing, and Tracking Masked Human Face

A surveillance system is still the most exciting and practical security system to prevent crime effectively. The primary purpose of this system is to recognize the identity of the face caught by the camera. With the advancement of the Internet of things, surveillance systems were implemented on edge devices such as the low-cost Raspberry mobile camera. It raises the challenge of unstructured image/video where the video contains low quality, blur, and variations of human poses. The challenge is increasing because people used to wear a mask during the Covid -19 pandemic.  Therefore, we proposed developing an all-in-one surveillance system with face detection, recognition, and face tracking capabilities. This system integrated three modules: MTCNN face detector, VGGFace2 face recognition, and Discriminative Single-Shot Segmentation (D3S) tracker to create a system capable of tracking the faces of people caught on surveillance camera. We also train new face mask data to recognize and track. This system obtains data from the Raspberry Pi camera and processes images on the cloud as a mobile sensor approach. The proposed system successfully implemented and obtained competitive results in detection, recognition, and tracking under an unconstrained surveillance camera

The Design of E-Commerce System to Increase Sales Productivity of Home Industry in Indonesia

The household industry is the foundation of the existing home industry in Indonesia. It is categorized as a type of Small and Medium Enterprises (MSMEs) that significantly influence the Gross Domestic Product (GDP) ratio by up to approximately 10%. Since the pandemic of Covid-19, the home industry has increasingly stretched, especially in culinary and home craft products. The internet is one of the efforts to increase household industry sales. The household industry needs e-commerce to be a container for marketing its products. In this paper, we design an e-commerce system to support the sales productivity of the household industry in Indonesia. This study's e-commerce system or application is developed through some crucial stages. The stages are analysis through a questionnaire that represents needs in the field, selection of business models, namely B2B models with Virtual Storefront, marketplace concentrators, and lastly, Information Broker. Our infrastructure is determined for e-commerce development, and then strategy analysis is done using portfolio analysis, SWOT analysis, and competitor analysis. Based on the proposed strategy, we made a prototype as a designed e-commerce system that can increase sales for household businesses in cities in Indonesia. Important features in our proposed e-commerce system can accommodate many sellers or the household industry to establish relationships with many buyers based on geographical location, product search features based on closest positions or by city, and product categorization by familiar categories with household products.

SISTEM KEAMANAN NILAI AKADEMIK ONLINE BERBASIS KODE HASH DENGAN IDENTITAS SERVER SEBAGAI PARAMETER VALIDASI STUDI KASUS: SISTEM DATA NILAI AKADEMIK FAKULTAS TEKNIK – UNIVERSITAS MATARAM

Pada Sistem Informasi Akademik  Fakultas Teknik Universitas Mataram (SIA FT Unram) dimungkinkan adanya pihak tidak berwenang untuk mengubah data akademik mahasiswa. Hal ini dikarenakan data akademik mahasiswa disimpan dalam bentuk teks biasa pada basis data server SIA FT Unram. Pengubahan nilai akademik secara illegal ini tentunya dapat merugikan banyak pihak. Keamanan data yang disimpan pada basis data SIA FT Unram merupakan suatu aspek yang perlu dijaga. Keamanan data SIA FT Unram berguna untuk menciptakan system informasi yang dapat menjaga privasi dan validitas data yang disimpan. Pada penelitian ini dibangun system pengamanan informasi penting pada basis data SIA FT Unram menggunakan metode encryption of data in motion. Metode yang digunakan pada penelitian ini berbasis kode hash sebagai kode validasi keabsahan suatu nilai akademik .Metode ini memetakan data akademik mahasiswa menjadi string dengan panjang yang tetap. Pada metode ini dilakukan pengkodean terhadap suatu nilai akademik menggunakan identitas server dan beberapa variabel lain sebagai parameter. Fokus utama penelitian ini adalah untuk mengembangkan system pengamanan data nilai akademik yang cepat dan aman. Kode hash yang dihasilkan pada penelitian ini memiliki panjang 98 karakter. Waktu eksekusi pembuatan kode hash kurang dari 1 detik untuk 10 data nilai akademik mahasiswa. Hasil penelitian menunjukkan bahwa system keamanan yang dibangun telah dapat mengamankan data nilai akademik SIA FT Unram. Metode yang dikembangkan pada penelitian ini juga terbukti tidak mengurangi waktu kerja SIA FT Unram secara signifikan. Kata Kunci: Sistem keamanan, data akademik,enkripsi, has

Pemanfaatan Free Apps dan Open-source Software sebagai Alternatif Pembelajaran Online SD Negeri 1 Terong Tawah

SD Negeri 1 Terong Tawah is an elementary school with an A accreditation and has implemented the 2013 curriculum (K-13). Along with implementing learning from home during the Covid-19 Pandemic, SDN 1 Terong Tawah has not implemented e-learning due to limited resources. Not all students have adequate devices to access the internet. This causes the learning process to be not optimal. In addition, the teachers of SD Negeri 1 Terong Tawah and academic staff are not familiar with online learning. In this case, the teachers are required to be able to manage creative content so that the online-based learning media that is applied can be easily understood and enjoyable to use, and no less important. The application is used, which must answer the problem, where every student does not all have a smartphone device. Through training activities on the use of e-learning that is open source, it is expected to be a solution that can answer the questions faced, where the applications developed are free media and can be opened on various internet-connected devices such as laptops/computers/smartphones, are web-based so that no installation process required