PDF Proceedings of the - Universiti Malaysia Sarawak

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Proceedings of the

2021 IEEE International Conference on Signal and Image Processing Applications (IEEE ICSIPA 2021)

Kuala Terengganu, Malaysia (Virtual) September 13 - 15, 2021

IEEE Signal Processing Society Malaysia Chapter

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ii Copyright and Reprint Permission:

Abstracting is permitted with credit to the source. Libraries are permitted to photocopy beyond the limit of U.S. copyright law for private use of patrons those articles in this volume that carry a code at the bottom of the first page, provided the per-copy fee indicated in the code is paid through Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923. For reprint or republication permission, email to IEEE Copyrights Manager at pubs- [email protected]. All rights reserved. Copyright ©2021 by IEEE.

IEEE Catalog Number: CFP2173I-ART ISBN: 978-1-6654-3592-5

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Conference Program

Day 1 - Monday, 13

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September 2021

Track 1: Computer Vision Processing and Analysis I

Development of a Deep Learning Model to Classify X-Ray of COVID-19, Normal and Pneumonia- Affected Patients

Boon Kai Law and Lih Poh Lin

Deep Learning Radio Frequency Signal Classification with Hybrid Images Hilal Elyousseph and Majid L Altamimi

Sparse Checkerboard Corner Detection from Global Perspective Jiwoo Kang, Hyunse Yoon, Seongmin Lee and Sanghoon Lee

Fusion of 2.5D Face Recognition through Extreme Learning Machine via Manifold Flattening Lee-Ying Chong and Siew Chin Chong

Training Convolutional Neural Networks to Detect Waste in Train Carriages Nathan Western, Xianwen Kong and Mustafa Erden

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Track 2: Speech & Music Processing

An Insight Into the Rise Time of Exponential Smoothing for Speech Enhancement Methods Siow Yong Low

Spoken Malay Profanity Classification Using Convolutional Neural Network

Abdulaziz Saleh Ba Wazir, Hezerul Abdul Karim, Nouar AlDahoul, Mohd Haris Lye Abdullah, Sarina Mansor, Mohammad Faizal Ahmad Fauzi, Sui Lyn Hor and Tabibah Zainab Zulkifli Automatic Diagnosis and Prediction of Cognitive Decline Associated with Alzheimer's Dementia through Spontaneous Speech

Ziming Liu, Lauren Proctor, Parker Collier and Xiaopeng Zhao

Monaural Speech Enhancement using Deep Neural Network with Cross-Speech Dataset Norezmi Jamal, Shahnoor Shanta, Norfaiza Fuad, N. Fuad and Mohd Nurul Al-Hafiz Sha'abani Emotion Recognition Using Bahasa Malaysia Natural Speech

Afiq Aiman Ahmad Fairuz Rizal and Nik Nur Wahidah Nik Hashim

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Track 3: Computer Vision Processing and Analysis II Affect recognition using dynamic characteristics of motion

Saba Baloch, Syed A.R. Abu Bakar, Musa Mohd Mokji and Saima Waseem

A Comparative Study of In-Domain vs Cross-Domain Learning for Porn Cartoon Classification Nouar AlDahoul, Hezerul Abdul Karim, Abdulaziz Saleh Ba Wazir, Mhd Adel Momo and Mohd Haris Lye Abdullah

Classification of Digital Chess Pieces and Board Position using SIFT Brandon Sean Kong, Irwandi Hipiny and Hamimah Ujir

A Simplified Skeleton Joints Based Approach For Human Action Recognition Najeeb Ur Rehman Malik, Syed A.R. Abu Bakar and Usman Ullah Sheikh

Electroencephalogram Stress Classification of Single Electrode using K-means Clustering and Support Vector Machine

Yi Wen Tee, Siti Armiza Mohd Aris, Siti Zura A. Jalil and Sahnius Usman

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Track 4: Image Enhancement & Restoration

A study on staircase artifacts in total variation image restoration Tarmizi Adam, Mohd Fikree Hassan and Raveendran Paramesran

Image to image translation network using perceptual adversarial loss function

Saleh Altakrouri, Sahnius Usman, Norulhusna Ahmad, Taghreed Justinia and Norliza Mohd Noor Rewritable Data Embedding in image based on Improved Coefficient Recovery

Alan Sii, Simying Ong, Mee Chin Wee and KokSheik Wong

Nom Document Background Removal Using Generative Adversarial Network Loc Tan Ho, Thai Son Tran and Dinh Dien

IRPMID: Medical XRAY Image Impulse Noise Removal using Partition Aided Median, Interpolation and DWT

Mohamed Shajahan, Siti Armiza Mohd Aris, Sahnius Usman and Norliza Mohd Noor

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Day 2 - Tuesday, 14

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September 2021

Track 5: Image Segmentation

Region Detection Rate: An Applied Measure for Surface Defect Localization Tamino Huxohl and Franz Kummert

Dynamic U-Net Using Residual Network for Iris Segmentation Nurul Amirah Mashudi, Norulhusna Ahmad and Norliza Mohd Noor Malaria Parasite Detection using Residual Attention U-Net

Chiang Kang Tan, Goh Chuan Meng, Sayed Ahmad Zikri Bin Sayed Aluwee, Khor Siak Wang Khor and Meei Tyng Chai

A Robust Segmentation of Malaria Parasites Detection using Fast k-Means and Enhanced k-Means Clustering Algorithms

Thaqifah Ahmad Aris, Aimi Salihah Abdul Nasir and Zeehaida Mohamed

Road Traffic Sign Detection and Recognition using Adaptive Color Segmentation and Deep Learning

Roozbeh KhabiriKhatiri, Idris Abd. Latiff and Ahmad Sabry Mohamad

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Track 6: Biomedical Signal Processing & Health Informatics

Design and Optimization of Homomorphic Medical Image Fusion Algorithm

Mat Kamil Awang, Muhammad Aliff Haiqal Mohd Marzuki and Nurul Kamilah Mat Kamil Camera-Based Remote Photoplethysmography for Physiological Monitoring in Neonatal Intensive Care

Benjamin Sweely, Ziming Liu, Tami Wyatt, Katherine Newnam, Hairong Qi and Xiaopeng Zhao

An Adaptive Data Processing Framework for Cost-Effective COVID-19 and Pneumonia Detection Kin Wai Lee and Renee Ka Yin Chin

Dynamic Modeling of COVID-19 Disease with an Impact of Lockdown in Pakistan & Malaysia Ghulam E Mustafa Abro, Saiful A Zulkifli, Vijanth Sagayan Asirvadam, Nirbhay Mathur, Rahul Kumar and Vipin Kumar Oad

Inclusion of Climate Variables for Dengue Prediction Model: Preliminary Analysis

Loshini Thiruchelvam, Sarat Chandra Dass, Nirbhay Mathur, Vijanth Sagayan Asirvadam and Balvinder Gill

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Track 7: Object Detection & Tracking

Comparison of Dental Caries Level Images Classification Performance using KNN and SVM Methods

Yessi Jusman, Muhammad Khoirul Anam, Sartika Puspita, Edwyn Saleh, Siti Nurul Aqmariah Mohd Kanafiah and Rhesezia Intan Tamarena

Estimation of Leaf Area in Bell Pepper Plant using Image Processing techniques and Artificial Neural Networks

Vahid Mohammadi, Saeid Minaei, Ali Reza Mahdavian, Mohammad Hadi Khoshtaghaza and Pierre Gouton

Identification of the writer of historical documents via geometric modeling of the handwriting Dimitrios Arabadjis, Constantin Papaodysseus and Athanasios Rafail Mamatsis

Comparative Analysis of Explainable Artificial Intelligence for COVID-19 Diagnosis on CXR Image

Joe Huei Ong, Kam Meng Goh and Li Li Lim

An Evaluation of State-of-the-Art Object Detectors for Pornography Detection

Sui Lyn Hor, Hezerul Abdul Karim, Mohd Haris Lye Abdullah, Nouar AlDahoul, Sarina Mansor, Mohammad Faizal Ahmad Fauzi, John See and Abdulaziz Saleh Ba Wazir

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Track 8: Trending Technologies in Signal and Image Processing

Modeling, Controlling & Stabilization of An Underactuated Air-Cushion Vehicle (ACV) Ghulam E Mustafa Abro, Saiful A Zulkifli, Vijanth Sagayan Asirvadam, Zain Anwar Ali, Nirbhay Mathur and Rahul Kumar

A Smart Flight Controller based on Reinforcement Learning for Unmanned Aerial Vehicle (UAV) Fawad Salam Khan, Mohd Norzali Haji Mohd, Susama Bagchi, Raja Masood Larik, Muhammad Inam Abbasi and Muhammad Khan

Unified Discriminant and Distribution Alignment for Visual Domain Adaptation M. S. Rizal Samsudin, Syed A.R. Abu Bakar and Musa Mohd Mokji

Active Stereo Matching Benchmark for 3D Reconstruction using Multi-view Depths Mingyu Jang, Seongmin Lee, Jiwoo Kang and Sanghoon Lee

Personal Protective Equipment Detection with Live Camera Ng Wei Bhing and Patrick Sebastian

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Day 3 - Wednesday, 15

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September 2021

Track 9: Applied Signal, Image and Speech Processing

A fast and unbiased minimalistic resampling approach for the particle filter Ramakrishna Gurajala, Praveen Choppala, James Stephen and Paul D Teal Short-term power prediction using ANN

Gulnar Perveen, Priyanka Anand and Amod Kumar

A Critical Review on Water Level Measurement Techniques for Flood Mitigation Obaid Rafiq Jan, Hudyjaya Siswoyo Jo and Riady Siswoyo Jo

Local File Inclusion Vulnerability Scanner with TOR Proxy

Ku Ahmad Haziq Hezret Che Ku Mohd Sahidi, Muhammad Azizi Mohd Ariffin, Muhammad Izzad Ramli and Zolidah Kasiran

Hybrid Combiner Circuit Of MNOs For Capacity Enhancement Solution In Indoor Environment Suzi Seroja Sarnin, Wan Norsyafizan W. Muhamad, Naim Nani Fadzlina and Ros Shilawani S.

Abdul Kadir

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Class 1 and Class 2 Underwater Image Enhancement And Restoration Under Turbidity Conditions Mat Kamil Awang, Halimatun Saidah Aminuddin, Nurul Kamilah Mat Kamil and Kamarul 'Asyikin Mustafa

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Authors Index 262

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Position using SIFT

Brandon Sean Kong Faculty of Computer Science & IT

Universiti Malaysia Sarawak Kota Samarahan, Malaysia [email protected]

Irwandi Hipiny

Faculty of Computer Science & IT Universiti Malaysia Sarawak

Kota Samarahan, Malaysia [email protected]

Hamimah Ujir

Faculty of Computer Science & IT Universiti Malaysia Sarawak

Kota Samarahan, Malaysia [email protected]

Abstract—Assistive technology has been given more attention in recent years to help people with disabilities to perform common tasks. Rather than designing a specialised tool for the task, it is more cost-effective and less inhibitory to make use of existing hardware integrated with a smart interface. Towards this end goal, we present our work on assisting a visually impaired person playing an online chess game. We evaluated an invariant feature descriptor, i.e., SIFT, for the task of classifying individual chess pieces across multiple visual themes. We compared two strategies for building the visual codebook, i.e., k-means clustering vs. image blending. The proposed pipeline receives live screen feeds from the browser at a fixed interval and produces an output in the form of chess pieces’ label and board position. Our proposed pipeline, paired with a visual codebook built using k-means clustering, managed an average accuracy rate of 6/10.

Keywords—chess, classification, scale-invariant feature transform (SIFT)

I. INTRODUCTION

Chess is a one of the oldest board games that is still popular today. Throughout the centuries, it has evolved through many variations and the current popular medium for playing it is via ranked online matches. We focus on image- based classification of digital chess pieces inside screen grabs of these chess-playing websites with the motivation of helping the visually impaired group to seamlessly participate in matches. Screen grabs are captured at a fixed interval and fed to the built prototype. The prototype returns the chess pieces’

label and board position. This information can be relayed back to the user via audio feedback. The goal of this research is to create a universal interface that will work with most chess- playing websites, regardless of the screen layout and visual theme.

According to [1], recognition of chess pieces and chessboards is still an open research problem in the Computer Vision community. Recent work had utilised deep learning models such as Convolutional Neural Network (CNN) and regular machine learning algorithms such as Support Vector Machine (SVM). The latter is typically trained using Lowe’s Scale-invariant Feature Transform (SIFT) [2] or Dalal and Triggs’ Histogram of Oriented Gradients (HOG) [3]. CNN is widely used for image classification task involving large-scale datasets and a wide number of categories, for example [4] and [5]. Models employing handcrafted features such as SIFT and HOG are typically used for category-specific dataset, for

example, animal re-ID [6][7][8], handwritten characters [9][10] and plant species identification [11].

II. BACKGROUND

The core component of our prototype is the feature matching algorithm. The algorithm is very important to ensure that the prototype can reliably classify the chess pieces, as well as estimating their individual board position. This subsection starts with a review of the seminal work on invariant feature descriptors, followed by a summary of existing work on chess piece classification.

A. Invariant Feature Descriptors

1) Oriented FAST and Rotated BRIEF (ORB): ORB [12]

is constructed from Features from Accelerated Segment Test (FAST) keypoint detector, and modified Binary Robust Independent Elementary Features (BRIEF) descriptor. The algorithm uses modified BRIEF descriptor due to the BRIEF descriptor being unstable during rotation-invariant cases.

2) Binary Robust Invariant Scalable Keypoints (BRISK):

BRISK [13] describes a keypoint by identifying its characteristic direction hence making the descriptor rotation- invariant.

3) Scale-invariant Feature Transform (SIFT): SIFT [2]

locates the keypoints by finding scale-space extrema inside a given image. SIFT uses 2x2 Hessian matrix to eliminate keypoints found around the edges. The resulting descriptor contains magnitude and orientation of gradient inside 4x4 subregions surrounding the keypoint. Each subregion consists of 8 orientation bins, thus producing a 4x4x8=128-bit descriptor.

B. Quantitative Comparison

TABLE I. COMPARISON OF FEATURE DESCRIPTORS [14].

Criteria Rank

Feature Matching Time per Keypoint SIFT > BRISK > ORB Outlier Rejection and Homography

Fitting Time per Keypoint SIFT > BRISK > ORB Total Image Matching Time SIFT > BRISK > ORB Accuracy of Image Matching ORB > BRISK > SIFT