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All Journal Jurnal Kesehatan Masyarakat BISNIS: Jurnal Bisnis dan Manajemen Islam Jurnal Informatika dan Teknik Elektro Terapan JOIV : International Journal on Informatics Visualization Al-Mashlahah: Jurnal Hukum Islam dan Pranata Sosial Al Mi’yar: Jurnal Ilmiah Pembelajaran Bahasa Arab dan Kebahasaaraban Martabe : Jurnal Pengabdian Kepada Masyarakat IJID (International Journal on Informatics for Development) Ensiklopedia of Journal Buletin Poltanesa Jurnal Kajian Ekonomi dan Pembangunan Fikruna : Jurnal Ilmiah Kependidikan dan Kemasyarakatan Journal of Language, Literature, and Arts (JoLLA) PUSKAPSI Law Review At-Tadzkir: Islamic Education Journal OMNICODE Journal (Omnicompetence Community Developement Journal) Biner : Jurnal Ilmu Komputer, Teknik dan Multimedia Al Mu'azarah: Jurnal Pengadian kepada Masyarakat Maqashiduna: Jurnal Hukum Keluarga Islam Jurnal Ilmiah Kesehatan Sandi Husada Media Riset Ekonomi Pembangunan (MedREP) SIMAS JURNAL PENGABDIAN MASYARAKAT
Muhammad Anshari, Muhammad
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Neuroscience Nursing Public Health Social Sciences Transportation Other

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Journal : JOIV : International Journal on Informatics Visualization

 1 
Skew Correction and Image Cleaning Handwriting Recognition Using a Convolutional Neural Network Uyun, Shofwatul; Rahardyan, Seto; Anshari, Muhammad
JOIV : International Journal on Informatics Visualization Vol 7, No 3 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.3.1712

Abstract

Handwriting recognition is a study of Optical Character Recognition (OCR) which has a high level of complexity. In addition, everyone has a unique and inconsistent handwriting style in writing characters upright, affecting recognition success. However, proper pre-processing and classification algorithms affect the success of pattern recognition systems. This paper proposes a pre-processing method for handwriting image recognition using a convolutional neural network (CNN). This study uses public datasets for training and private datasets for testing. This pre-processing consists of three processes: image cleaning, skew correction, and segmentation. These three processes aim to clean the image from unnecessary ink streaks. In addition, to make angle corrections to characters in italics in their writing. The model testing process uses image test data of handwriting that are not straight. There are three images based on the inclination angle: less than 45 degrees, equal to 45 degrees, and more than 45 degrees. Picture cleaning removes unnecessary strokes (noise) from the image using a layer mask, whereas skew correction changes the handwriting to an upright posture based on the detected angle. The pre-processing model we propose worked optimally on handwriting with a skew angle of fewer than 45 degrees and 45 degrees. Our proposed model generally works well for handwriting with fewer than 45 degrees skew with an accuracy of 88,96%. Research with a similar scope can continue to improve optimization with a focus on algorithms related to analysis layout studies. Besides that, it can focus more on automation in the segmentation process of each character.
Co-Authors ., Rusliyawati Achir Yani S. Hamid Adams, Hafizh Agustini, Shenti Amalia Aprianty, Rizqi Amalia Safitri Ardli, Ahmad Qolbi Arifin, Ahmad Fauzan Ariyani, Herda Aziza Fitriah, Aziza Chatarina Umbul Wahyuni Dewi Nurhanifah, Dewi Dhara Alim Cendekia Diana Aipipidely Diniati, Anna Dwi Kartikasari Dwi Oktaviana, Annisa Esti Yunitasari Fandiny, Yeny  Fathullah, M. Rizqi Fitri Syahrida, Anisa Fitri, Winda Gunawan, Eko Hadi Habibah, Aina Hadi Prayitno, Hadi Haluruk, John Davison Haryono Haryono Heru Santoso Wahito Nugroho hidayatullah Al Islami Hilal Dzakwan, Muhammad Ibnu Adhan, Alvito Juanda Astarani Khairunnisa, Monica Khairunnisa, Najla Lailan Azima, Siti Laisa, Alya Latifah Latifah Lutfi Arianto, Ach Mahridawati, Mahridawati Mardiani, Vivi Maria Ulfah Siregar Mitra Istiar Wardhana, Mitra Istiar Mohammad Nabil Almunawar, Mohammad Nabil Mubarak, Muhammad Rusydi Muhamad Arif Muhammad Erfan, Muhammad Muhammad Rizqi Mulyani, Risya Mulyawan, Rizki Nabila, Alsha Natalia, Novi Naufal Rismana, Muhammad Ndungi, Rebeccah Nelonda, Selli Nor Azizah, Nor Norsehan, Norsehan Noviyanti Fatimah, Firni Nur Pramudyas, Maulinda Nurfadila Meywanda, Utin Nurochman Nurochman, Nurochman Nurrahmah, Medina Nurrifanti Dewi, Saputri Octaviani, Dian Patrick Kim Cheng Low, Patrick Kim Cheng Putri Anugrahni, Ridha Putri, Novita Rahmadani Qorirah, Sahla Rahardyan, Seto Rahim, Mohamad Marzuqi Abdul Rahmani, Dienny Redha Rahmawati, Riris Trimaulida Ramadhan, Ade Umar Ristya Widi Endah Yani Riza, Andika Ahmad Satria, Doni Setiawan, Firman Setiawati Hariyono, Dyta Setyobudi, Agus Shofwatul ‘Uyun Siti Mutmainah Sumardi, Wardah Haki Haji Syahrina, Wanda Syifaun Nafisah Trisetyo, Febiola Anggun Ulfah, Pitria Utami, Mega Dewi Sri Yantiana, Nella Yunita Satya Pratiwi Zahra, Fatimatul Zahra, Raudhatuz