6 research outputs found
Sanal heykeltraşlıkta optimize edilmiş hash-temelli octree veri yapısının kullanılması
06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Sanal heykeltıraşlık, kullanıcılara sanat, tasarım ve hızlı prototipleme alanlarında sanal gerçeklik donanım ve yazılımları tarafından sağlanan bir sanal dünya içerisinde yeni 3B katı nesne oluşturma veya mevcut nesneleri değiştirebilme imkânı sağlayan 3B bir modelleme işlemidir. Bu tez çalışmasında haptic kuvvet geri-beslemesi ile voksel-temelli bir sanal heykeltıraşlık uygulaması için optimize edilmiş hash-temelli bir octree veri yapısı kullanımı önerilmektedir. Amaç, hacim voksel veri kümesini saklamak için gerekli hafızayı ve hesaplama maliyetini düşürmek, aynı zamanda da gerçek-zamanda etkileşim esnasında gerçekleşen octree kullanımından doğan ağaç dolanım süresini azaltarak model yüzeyinin lokal olarak yeniden oluşturulma süresini kısaltmaktır. İlk önce, üzerinde çalışılan sanal ham maddeye ait hacim verisi daha az hafıza kullanarak saklayabilmek ve gerçek-zamanda yontabilmek amacıyla vokselleştirilerek optimize-edilmiş hash-temelli bir octree veri yapısına dönüştürülmektedir. Daha sonra, küre olarak tasarlanan sanal araç tarafından heykelin hangi voksellerine dokunulduğu belirlenerek bu vokseller veri yapısından çıkarılmaktadır. Sonuç verisine gerçekçi bir görüntü verebilmek amacıyla üçgen kafes modelini yeniden oluşturmak için Marching Cubes algoritması kullanılmaktadır. Tüm hacim için hesaplama maliyeti yüksek olduğundan dolayı bu çalışmada sadece yontma işleminden sonra modifiye edilen vokseller tarafından etkilenen eş yüzey yeniden hesaplanarak lokal güncelleme gerçekleştirildi. İkinci olarak, önerilen sanal heykeltıraşlık sistemine, sanal yontma aracının üç-boyutlu kontrolünü sağlamak ve kullanıcıların yontma işlemi sırasında heykel üzerinde uyguladıkları kuvvete karşı meydana gelen direnci hissedebilmelerine imkan sağlamak amacıyla bir haptic cihazı yolu ile haptic kuvvet-geri beslemesi entegre edilmiştir. Sanal heykeltıraşlıkta hafıza optimizasyonu ve gerçek-zaman etkileşimi üzerine odaklanılan bu çalışmada, önerilen optimize edilmiş hash-temelli octree veri yapısının performansını test etmek amacıyla hafıza maliyetleri ve çalışma süreleri, işaretçi-temelli ve hash temelli veri yapıları ile karşılaştırılmıştır. Sonuç olarak, bu yeni optimize edilmiş hash-temelli octree veri yapısının hem ön-işleme zamanında hem de gerçek zamanda hafıza maliyetleri ve çalışma sürelerindeki düşüşler gösterilmiştir. Anahtar kelimeler: Sanal Heykeltaşlık, Haptics, Vokselleştirme, Octree, HashingVirtual sculpting is a 3D modelling process which allows users to create new 3D solid models or modify existing objects provided by virtual reality software and hardware in art, design and rapid prototyping areas. In this thesis, an optimized hash-based octree data structure in a voxel-based virtual sculpting application with haptic force feedback is proposed. The goal is to reduce the memory and computation costs to store volumetric voxel dataset and also to reduce the local surface reconstruction times of the model by decreasing tree traversal time caused by octree during real-time interaction. First, in order to store with less memory and carve in real-time, volumetric data of virtual workpiece is converted into an optimized hash-based octree data structure by voxelizing them. Then, voxels collided with the carving tool that is designed as a sphere are removed from this data structure. Marching Cubes algorithm is used to reconstruct the triangular mesh model in order to give a realistic display of the voxel data. Since the computational cost is very high for the whole volume, in this study, local update is performed by reconstructing the isosurface affected from the modified voxels after carving process. Afterwards, by the way of a haptic device, a haptic force feedback is integrated in the proposed virtual sculpting application in order to provide 3D control of the virtual tool and allow to feel the resistance against the applied force on the sculpture object. This study focused on memory optimization and real-time interaction, memory costs and runtimes of the proposed optimized hash-based octree data structure are compared with the pointer-based and hash-based ones in order to test the performance. Consequently, memory cost and working time decreases on both pre-processing and runtime of this new optimized hash-based octree data structure are shown. Keywords: Virtual Sculpting, Haptics, Voxelization, Octree, Hashin
A real-time virtual sculpting application with a haptic device
In this paper, a 3D virtual sculpting application is developed for 3D virtual models with removing or adding materials by using Boolean operations. Virtual sculpting simulation reads 3D virtual models in a variety of file formats such as raw and stl consisting of a triangle poligon mesh and voxelizes its outer surface and interiror volüme to generate its volumetric dataset. We used octree and hashing techniques to reduce the memory requirement needed for volumetric dataset. The surface is locally reconstructed using Marching Cubes algorithm known as the most popular isosurface extraction algorithm after removing or adding material to the 3D virtual model. The user interacts with the model by using a haptic device to give the force-feedback like real-life sculpting.Publisher's Versio
A real-time virtual sculpting application by using an optimized hash-based octree
Creation durations of a traditional octree, a hash-based octree, and our optimized hash-based octree are compared. Tree traversal and surface reconstruction times of our optimized hash-based octree approach are also compared with the pointer-based one in off-line and real-time while sculpting a 3D model. It is shown that the memory requirement and durations of our optimized approach are the lowest.https://doi.org/10.3906/elk-1401-25
LIBRARY AUTOMATION DESIGN FOR VISUALLY IMPAIRED PEOPLE
Speech synthesis is a technology used in many different areas in computer science. This technology can bring a solution to reading activity of visually impaired people due to its text to speech conversion. Based on this problem, in this study, a system is designed needed for a visually impaired person to make use of all the library facilities in Sakarya University. Certain number of books in the library is transferred in digital media via a scanner and they are transferred into their own server. A visually impaired person can use the system with the help of sound orientation of the program and the keyboard commands of the user. System will be developed according to new requests. So, the purpose of this study is to bring a solution to the social problem of visually impaired people
LIBRARY AUTOMATION DESIGN FOR VISUALLY IMPAIRED PEOPLE
Speech synthesis is a technology used in many different areas in computer science. This technology can bring a solution to reading activity of visually impaired people due to its text to speech conversion. Based on this problem, in this study, a system is designed needed for a visually impaired person to make use of all the library facilities in Sakarya University. Certain number of books in the library is transferred in digital media via a scanner and they are transferred into their own server. A visually impaired person can use the system with the help of sound orientation of the program and the keyboard commands of the user. System will be developed according to new requests. So, the purpose of this study is to bring a solution to the social problem of visually impaired people
Deep Learning-Based Classification of Dermoscopic Images for Skin Lesions
Skin cancer has emerged as a grave health concern leading to significant mortality rates. Diagnosis of this disease traditionally relies on specialist dermatologists who interpret dermoscopy images using the ABCD rule. However, the integration of computer-aided diagnosis technologies is gaining popularity as a means to assist clinicians in accurate skin cancer diagnosis, overcoming potential challenges associated with human error. The objective of this research is to develop a robust system for the detection of skin cancer by employing machine learning algorithms for skin lesion classification and detection. The proposed system utilizes Convolutional Neural Network (CNN), a highly accurate and efficient deep learning technique well-suited for image classification tasks. By using the power of CNN, this system effectively classifies various skin diseases in dermoscopic images associated with skin cancer The MNIST HAM10000 dataset, comprising 10015 images, serves as the foundation for this study. The dataset encompasses seven distinct skin diseases falling within the realm of skin cancer. In this study, diverse transfer learning methods were used and evaluated to enhance the performance of the system. By comparing and analyzing these approaches the highest accuracy rate was obtained using the MobileNetV2 model with a rate of 80.79% accuracy