Search Results - (( edge detection means algorithm ) OR ( based optimization model algorithm ))*

Detecting lung cancer region from CT image using meta-heuristic optimized segmentation approach by Shakeel, Pethuraj Mohamed, Mohd Aboobaider, Burhanuddin, Salahuddin, Lizawati

“…In this paper, the butterfly optimization algorithm-based K-means clustering (BOAKMC) method is introduced for reducing CT image segmentation uncertainty. …”
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Model-based hybrid variational level set method applied to object detection in grey scale images by Wang, Jing

“…In industrial inspection, segmentation algorithms detect product defects, cracks, or anomalies for quality control and safety. …”
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Modified canny edge detection technique for joining discontinued edges by S. K. T. Hwa, Abdullah Bade, Mohd Hanafi Ahmad Hijazi

“…The Canny edge detection technique is regarded as one of the most successful edge detection algorithms because of the good edge detection effect. …”
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Modified canny edge detection technique for identifying endpoints by Kieu, STH, Abdullah Bade, Mohd Hanafi Ahmad Hijazi

“…The Canny edge detection technique is regarded as one of the most successful edge detection algorithms because of the good edge detection effect. …”
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The application of Hough Transform for corner detection by Jamaludin, Mohad Fuad

“…Mean while, the Zhang Suen Thinning Method can be used to reduce the edge points into minima points to speed up the algorithm. …”
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Lane detection system for autonomous vehicle using image processing techniques by Mohd Kiblee, Shahizul Eza

“…Since the strongest characteristic of a road marking image are the edges, the road marking detection step is based on edge detection. …”
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Profile Reconstruction Utilizing Forward-Backward Time-Stepping With the Integration of Automated Edge-Preserving Regularization Technique for Object Detection Applications by Yong, G., Ping, K.A.H., Sahrani, S., Marhaban, M.H., Sariphan, M.I., Moriyama, T., Takenaka, T.

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Crypt Edge Detection Using PSO,Label Matrix And BI-Cubic Interpolation For Better Iris Recognition(PSOLB) by Hashim, Nurul Akmal

“…Recently,there has been renewed interest in iris features detection.Gabor filter,cross entrophy, upport vector,and canny edge detection are methods which produce iris codes in binary codes representation.However,problems have occurred in iris recognition since low quality iris images are created due to blurriness,indoor or outdoor settings, and camera specifications.Failure was detected in 21% of the intra-class comparisons cases which were taken between intervals of three and six months intervals.However,the mismatch or False Rejection Rate (FRR) in iris recognition is still alarmingly high.Higher FRR also causes the value of Equal Error Rate (EER) to be high.The main reason for high values of FRR and EER is that there are changes in the iris due to the amount of light entering into the iris that changes the size of the unique features in the iris.One of the solutions to this problem is by finding any technique or algorithm to automatically detect the unique features.Therefore a new model is introduced which is called Crypt Edge Detection which combines PSO,Label Matrix,and Bi-Cubic Interpolation for Iris Recognition (PSOLB) to solve the problem of detection in iris features.In this research, the unique feature known as crypts has been chosen due to its accessibility and sustainability.Feature detection is performed using particle swarm optimisation (PSO) as an algorithm to select the best iris texture among the unique iris features by finding the pixel values according to the range of selected features.Meanwhile, label matrix will detect the edge of the crypt and the bi-cubic interpolation technique creates sharp and refined crypt images.In order to evaluate the proposed approach,FAR and FRR are measured using Chinese Academy of Sciences' Institute of Automation (CASIA) database for high quality images.For CASIA version 3 image databases, the crypt feature shows that the result of FRR is 21.83% and FAR is 78.17%.The finding from the experiment indicates that by using the PSOLB,the intersection between FAR and FRR produces the Equal Error Rate (EER) with 0.28%,which indicated that equal error rate is lower than previous value, which is 0.38%.Thus,there are advantages from using PSOLB as it has the ability to adapt with unique iris features and use information in iris template features to determine the user.The outcome of this new approach is to reduce the EER rates since lower EER rates can produce accurate detection of unique features.In conclusion,the contribution of PSOLB brings an innovation to the extraction process in the biometric technology and is beneficial to the communities.…”
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Application of Fuzzy C-Means with YCbCr and DenseNet-201 for Automated Corn Leaf Disease Detection by Chyntia Jaby, Entuni

“…Some of the existing methods of segmentation are K-Means, Otsu’s, edge-based segmentation, watershed segmentation, region growing, mean shift, maxflow mincut (MFMC) graph cut and regional colour segmentation. …”
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Metacarpal phantom radiograph edge detection using genetic algorithm gradient based genotype / Norharyati Md Ariff by Md Ariff, Norharyati

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An enhance embedding method using edge and textures detection for image steganography by Al-Maliki, Alaa Jabbar Qasim

“…By embedding in noisy zones using edge and texture detection which complicates feature extraction, making hidden information more secure and statistically less detectable than basic LSB matching techniques. …”
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Real-time vehicle counting using custom YOLOv8n and DeepSORT for resource-limited edge devices by Saadeldin, Abuelgasim, Rashid, Muhammad Mahbubur, Shafie, Amir Akramin, Hasan, Tahsin Fuad

“…The proposed system was able to achieve an average vehicle detection mean average precision (mAP) score of 97.5%, a vehicle counting accuracy score of 96.8% and an average speed of 19.4 frames per second (FPS), all while being deployed on a compact Nvidia Jetson Nano edge-computing device. …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

“…Instead of solving the original optimal control problem, the model-based optimal control problem is solved. …”
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Stereo Camera-Based Aerial Target Geolocation in a Ground-Based Platform Environment by Amir Hilmi Bin Ahmad Azizi

Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques by Lipu M.S.H., Hussain A., Saad M.H.M., Hannan M.A.

Enhancing Oil Palm Fruit Detection: A Comparative Analysis Of Yolo Algorithms by Ainul Hakim Fizal Sabillah, Hafizal Mohamad, Sagaya Sabestinal Amalathas, Seung Hwan Won, Muhammad Hakim Ahmad Sobri

Cloud-based lightweight detection of hardhat compliance based on YOLOv5 in power construction site by Wanbo, Luo

“…Furthermore, existing algorithms face challenges in complex work sites, such as detecting long-distance, occluded, dense, and low-light objects. …”
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Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics by Ullah, Wasif, Mohd Fadzil Faisae, Ab Rashid, Muhammad Ammar, Nik Mu’tasim

“…Besides this, CPU time for PSO was very high compared to other algorithms. In the future, other optimization algorithms will be tested for the CHFS model, such as Teaching Learning Based Optimization (TLBO) and the Crayfish Optimization Algorithm (COA).…”
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Modified minimum maximum exclusive mean filter by Marhaban, Mohammad Hamiruce, Jabir, Amjad Najim, Mohd Noor, Samsul Bahari

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Automatic segmentation of jaw from panoramic dental X-ray images using GVF snakes by Hasan, MM, Ismail, W, Hassan, R, Yoshitaka, A