Results 271 to 280 of about 22,214 (311)

Scale-Invariant Feature Transform (SIFT)

2016
Many real applications require the localization of reference positions in one or more images, for example, for image alignment, removing distortions, object tracking, 3D reconstruction, etc. We have seen that corner points1 can be located quite reliably and independent of orientation.
Wilhelm Burger, Mark J. Burge
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A Parallel Analysis on Scale Invariant Feature Transform (SIFT) Algorithm

2011
With explosive growth of multimedia data on internet, the effective information retrieval from a large scale of multimedia data becomes more and more important. To retrieve these multimedia data automatically, some features in them must be extracted. Hence, image feature extraction algorithms have been a fundamental component of multimedia retrieval ...
Donglei Yang, Lili Liu, Feiwen Zhu, Weihua Zhang   +3 more
openaire   +1 more source

Arca Detection and Matching Using Scale Invariant Feature Transform (SIFT) Method of Stereo Camera

2017 International Conference on Soft Computing, Intelligent System and Information Technology (ICSIIT), 2017
Arca refers to ancient statues, which belong to Indonesian National Heritage and should be preserved. They are made of stones and woods. Many of arcas found in Indonesia are damaged by human hands and natural disasters. One of the solutions to preserve them is by reconstructing them in form of digital data.
Aviv Yuniar Rahman, Surya Sumpeno, Mauridhi Hery Purnomo   +2 more
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Panoramic of Image Reconstruction Based on Geospatial Data using SIFT (Scale Invariant Feature Transform)

2019 International Seminar on Intelligent Technology and Its Applications (ISITIA), 2019
Reconstruction can mean the return of something in its place of origin, rearrangement of existing material and rearranged as it is or the original event. Where in this study used the SIFT, match and homography method. Based on the results of this experiment, it was able to reconstruct panoramic images.
Adi Hermansyah, Arif Nugroho, Arief Kurniawan, Supeno Mardi Susiki Nugroho, Eko Mulyanto Yuniarno   +4 more
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Scale Invariant Feature Transform (SIFT) Parametric Optimization Using Taguchi Design of Experiments

2010
Traditional SIFT methods require a priori of object knowledge in order to complete accurate feature matching. The usual means is via trained databases of objects. In order to be able to get the pose of an object, accurate object recognition is required.
Dominic R. Maestas, Ron Lumia, Gregory Starr, John Wood   +3 more
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Cat’s Nose Recognition Using You Only Look Once (Yolo) and Scale-Invariant Feature Transform (SIFT)

2018 IEEE 7th Global Conference on Consumer Electronics (GCCE), 2018
This paper proposes a cat recognition system through cat’s nose using You only look once (Yolo) and Scale-Invariant Feature Transform (SIFT). For first part, this system detects the nose of a cat image using Yolo. After the nose is detected, we recognize the cat’s nose using SIFT method and make sure that the nose has been recognized correctly.
Rifka Widyastuti, Chuan-Kai Yang
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Methods for Determining Nitrogen, Phosphorus, and Potassium (NPK) Nutrient Content Using Scale-Invariant Feature Transform (SIFT)

2020 8th International Conference on Information and Communication Technology (ICoICT), 2020
Nutrient Content NPK is macronutrient content that important for the growth of a plant. The measurement of NPK conducted periodically, but the measurement using laboratories test need a relatively long time. This Research is conducted to determine the nutrient content of the soil, consisting of nitrogen, phosphor, and calcium (NPK) using digital image ...
Raden Sumiharto, Ristya Ginanjar Putra, Samuel Demetouw   +2 more
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The use of scale invariant feature transform (SIFT) algorithms to identification garbage images based on product label

2017 3rd International Conference on Science in Information Technology (ICSITech), 2017
Garbage has become a serious problem, especially in major cities. Garbage basically contain elements of organics and non-organic mixed. In a large volume, the separation of organic and non-organic become difficult jobs and longer if done conventionally. Separation is the identification of objects with one another to be classified.
Wawan Setiawan, Asep Wahyudin, G. R. Widianto   +2 more
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Texture image classification using scale invariant feature transform (SIFT) method

AIP Conference Proceedings, 2023
Haider S. Kaduhm, Hameed M. Abduljabbar
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Research Progress of the Scale Invariant Feature Transform (SIFT) Descriptors

Journal of Convergence Information Technology, 2010
Yuehua Tao -, Youming Xia -, Tianwei Xu -, Xiaoxiao Chi -   +3 more
openaire   +1 more source