Search Results - (( using optimization method algorithm ) OR ( using computing matching algorithm ))*

Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

“…Block Matching Algorithm (BMA) is a technique used to minimize the computational complexity of motion estimation in video coding application. …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

“…By implementing optimization algorithm in image template matching, it is expected that the computation time can be reduced. …”
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Fast Template Matching Method based Optimized Sum of Absolute Difference Algorithm for Face Localization by brahim belhaouari, samir, Josefina Janier , Josefina, Nadir, Nourain

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Evaluation of dynamic programming among the existing stereo matching algorithms by Teo, Chee Huat, Nurulfajar, Abd Manap

“…The algorithm used on the dynamic programming is the global optimization which provides better process on stereo images like its accuracy and its computational efficiency compared to other existing stereo matching algorithms. …”
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Disparity map algorithm for stereo matching process using local based method by Gan, Melvin Yeou Wei

“…The proposed SVDM algorithm involves four stages which starts from matching cost computation. …”
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Application of Evolutionary Algorithm for Assisted History Matching by Zahari, Muhammad Izzat

“…Today, tremendous efforts are made to develop Automatic History Matching algorithms. While the automatic method focus on optimization which is normally computer based. …”
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A new function of stereo matching algorithm based on hybrid convolutional neural network by Hamid, Mohd Saad, Kadmin, Ahmad Fauzan, Abd Manap, Nurulfajar, Hamzah, Rostam Affendi, Abd Gani, Shamsul Fakhar, Herman, Adi Irwan

“…This paper proposes a new hybrid method between the learning-based and handcrafted methods for a stereo matching algorithm. …”
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Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin by Shamsudin, Farah Syadiyah

“…There will be two processes involved, which are feature extraction using minutiae-based method and also the implementation of the proposed algorithm, CSA. …”
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Assisted History Matching by Using Genetic Algorithm and Discrete Cosine Transform by Abdul Rashid, Abdul Hadi

“…Back in the days, before computers and IT were widely used, history matching was done manually by trial and error method, where personal judgment were very critical in undergoing such methodology. …”
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Illumination-Invariant Image Matching Based on Simulated Kalman Filter (SKF) Algorithm by Nurnajmin Qasrina, Ann, Pebrianti, Dwi, Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Luhur, Bayuaji, Nor Rul Hasma, Abdullah

“…In order, the traditional algorithm to solve image matching problem take a lot of memory and computational time, image matching problem is assigned to optimization problem and can be solve precisely. …”
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Disparity map algorithm using hierarchical of bitwise pixel differences and segment-tree from stereo image by Zainal Azali, Muhammad Nazmi

“…In computer vision technology, stereo matching algorithm plays an important role in generating disparity map or depth map through a correspondence process from stereo images. …”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

“…In addition, the mentioned block-matching algorithms are the baseline techniques that have been used to further develop all the enhanced or improved algorithms. …”
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Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm by Jaber M.M., Yussof S., Elameer A.S., Weng L.Y., Abd S.K., Nayyar A.

Optimization of ANPR algorithm on android mobile phone by Mutholib, Abdul, Gunawan, Teddy Surya, Chebil, Jalel, Kartiwi, Mira

“…First, various steps to optimize ANPR and OCR block using template matching are described. …”
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Stereo Matching Based On Absolute Differences For Multiple Objects Detection by Hamzah, Rostam Affendi, Gan, Melvin Yeou Wei, Nik Anwar, Nik Syahrim

“…The first stage is matching cost computation to acquire preliminary result using an absolute differences method. …”
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HSV-template matching with MEESPSO algorithm for human tracking in a crowded environment by Nurul Izzatie Husna, Fauzi, Zalili, Musa

“…To address these issues, we introduced a new approach combining HSV-template matching with the MEESPSO algorithm. In this approach, HSV-template matching continuously detects the target object in sequence images, while the Midrange Exploration Exploitation Searching Particle Swarm Optimization (MEESPSO) algorithm searches for the target location in the frames. …”
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Enhanced Image View Synthesis Using Multistage Hybrid Median Filter For Stereo Images by Ali Hussein Aboali, Maged Yahya

“…Disparity depth map estimation of stereo matching algorithm is one of the most active research topics in computer vision.In the field of image processing,many existing stereo matching algorithms to obtain disparity depth map are developed and designed with low accuracy.To improve the accuracy of disparity depth map is quite challenging and difficult especially with uncontrolled dynamic environment.The accuracy is affected by many unwanted aspects including random noises,horizontal streaks,low texture,depth map non-edge preserving, occlusion,and depth discontinuities.Thus,this research proposed a new robust method of hybrid stereo matching algorithm with significant accuracy of computation.The thesis will present in detail the development,design, and analysis of performance on Multistage Hybrid Median Filter (MHMF).There are two main parts involved in our developed method which combined in two main stages.Stage 1 consists of the Sum of Absolute Differences (SAD) from Basic Block Matching (BBM) algorithm and the part of Scanline Optimization (SO) from Dynamic Programming (DP) algorithm.While,Stage 2 is the main core of our MHMF as a post-processing step which included segmentation,merging, and hybrid median filtering.The significant feature of the post-processing step is on its ability to handle efficiently the unwanted aspects obtained from the raw disparity depth map on the step of optimization.In order to remove and overcome the challenges unwanted aspects, the proposed MHMF has three stages of filtering process along with the developed approaches in Stage 2 of MHMF algorithm.There are two categories of evaluation performed on the obtained disparity depth map: subjective evaluation and objective evaluation.The objective evaluation involves the evaluation on Middlebury Stereo Vision system and evaluation using traditional methods such as Mean Square Errors (MSE),Peak to Signal Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM).Based on the results of the standard benchmarking datasets from Middlebury,the proposed algorithm is able to reduce errors of non-occluded and all errors respectively.While,the subjective evaluation is done for datasets captured from MV BLUE FOX camera using human's eyes perception.Based on the results,the proposed MHMF is able to obtain accurate results, specifically 69% and 71% of non-occluded and all errors for disparity depth map, and it outperformed some of the existing methods in the literature such as BBM and DP algorithms.…”
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Local Stereo Matching Algorithm Using Small-Color Census Spared Adaptive Support Weight by Nayan, M Yunus

“…This work is still on process, to test the algorithm; it will use the Middlebury benchmark. According to analysis of each step of the algorithms, the proposed SCCADSW can achieve good performance among stereo methods that rely on local optimization…”
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Shape matching and object recognition using dissimilarity measures with Hungarian algorithm by Chitra, D., Manigandan, T., Devarajan, N.

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Stereo matching algorithm using census transform and segment tree for depth estimation by Hamzah, Rostam Affendi, Zainal Azali, Muhammad Nazmi, Mohd Noh, Zarina, Tengku Wook, Tg Mohd Faisal, Zainal Abidin, Izwan

“…Fundamentally, the framework input is the stereo image which represents left and right images respectively. The proposed algorithm in this article has four steps in total, which starts with the matching cost computation using census transform, cost aggregation utilizes segment-tree, optimization using winner-takes-all (WTA) strategy, and post-processing stage uses weighted median filter. …”
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