Search Results - (( java implication based algorithm ) OR ( based evaluation matching algorithm ))

Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications by Teo, Chee Huat

“…Based on the results of evaluations, the results obtained by DSF is better than the algorithms, basic block matching and dynamic programming.…”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

“…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
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Stereo matching algorithm based on hybrid convolutional neural network and directional intensity difference by Hamid, Mohd Saad, Abd Manap, Nurulfajar, Hamzah, Rostam Affendi, Kadmin, Ahmad Fauzan

“…Hence, this article proposes a new stereo matching algorithm based on a hybrid Convolutional Neural Network (CNN) combined with directional intensity differences at the matching cost stage. …”
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Analysis of string matching compression algorithms by Nadarajan, Krishnaveny, Ahmad Zukarnain, Zuriati

“…The compression algorithms are string matching based which are LZW and LZSS. …”
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique by Hardev Singh, Jitvinder Dev Singh

“…In the video and frame selection, pre-defined video which have different type of motion and size is used for the algorithm evaluation purpose. The threshold calculation is based on the video selected. …”
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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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GPU-based odd and even hybrid string matching algorithm by Rahbari, Ghazal, Abdul Rashid, Nur’Aini, Husain, Wahidah

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Development Of Stereo-Matching Algorithm Based On Adaptive Weighted Prediction by Abd Razak, Siti Safwana

“…Therefore, to overcome the causes of effected accuracy, new Stereo Matching Algorithm (SMA) based on Adaptive Weighted Bilateral Filter (AWBF) was introduced together with characterize the SMA based on quantitative and qualitative measurements and produced SMA performance were evaluate using standard taxonomy of SM. …”
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Performance evaluation of automatic number plate recognition on android smartphone platform by Gunawan, Teddy Surya, Mutholib, Abdul, Kartiwi, Mira

“…For comparison purpose, the template matching based OCR will be compared to ANN based OCR. …”
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Steg Analysis Algorithm for Edge Adaptive Least Significant Bit Matching Revisited Detection by Edris, Khalid Edris, Fakhreldin, Mohammed Adam Ibrahim, Jasni, Mohamad Zain, Tuty Asmawaty, Abdul Kadir

“…The performance of the proposed steganalysis algorithm is evaluated and compared with five steganalysis algorithms. …”
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Text searching algorithm using boyer moore horspool (BMH) algorithm by Siti Nurafiqah, Jaafar

“…Based on the study, the average analysis result for this algorithm is 93% which is a strong match.…”
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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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Instance matching framework for heterogeneous semantic web content over linked data environment by Mansir, Abubakar

“…The evaluation is performed on real-world datasets provided in different Ontology Alignment Evaluation Initiative (OAEI) campaign as benchmark data for instance matching track evaluation. …”
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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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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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Disparity Refinement Process Based On Ransac Plane Fitting For Machine Vision Applications by Hamzah, Rostam Affendi, Kadmin, Ahmad Fauzan, Abd Gani, Shamsul Fakhar, Hamid, Mohd Saad, Salam, Saifullah

“…The framework is evaluated on three Middlebury datasets. The experimental results show that the proposed framework produces better-quality and more accurate than normal flow state-of-the-art stereo matching algorithms. …”
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Improvement Of Stereo Matching Algorithm Based On Sum Of Gradient Magnitude Differences And Semi-Global Method With Refinement Step by Hamzah, Rostam Affendi, Ibrahim, Haidi

“…A new stereo matching algorithm which uses improved matching cost computation and optimisation using the semi-global method (SGM) is proposed.The absolute difference is sensitive to low textured regions and high noise on the stereo images with radiometric distortions. …”
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A Comparative Analysis of Feature Extraction Algorithms for Augmented Reality Applications by Alam, Mir Suhail, Morshidi, Malik Arman, Gunawan, Teddy Surya, Olanrewaju, Rashidah Funke

“…The algorithms based on image feature detection and matching are critical in the field of computer vision. …”
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Image matching using relational graph representation by Lai, Chui Yen

“…Feature-based matching algorithm cannot tackle the problem of matching ambiguities easily. …”
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THE INVESTIGATION ON ARABIC WORD POSE ESTIMATION ALGORITHM AS MARKER FOR AUGMENTED REALITY APPLICATION by Mohd Zailani, Syarah Munirah, Morshidi, Malik Arman

“…Based on results obtained for the pattern matching technique performance on Arabic scripts, SURF shows a better accuracy rate and execution time compared to another algorithm. …”
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