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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Análise comparativa entre suportes para janelamento na técnica Shape From Focus

Silva, Marcelo Robson de Azevedo Martins da 27 September 2017 (has links)
Submitted by JOSIANE SANTOS DE OLIVEIRA (josianeso) on 2018-02-22T13:55:41Z No. of bitstreams: 1 Marcelo Robson de Azevedo Martins da Silva_.pdf: 3067819 bytes, checksum: d7b5c1e064c742114237189fe8cdc3d7 (MD5) / Made available in DSpace on 2018-02-22T13:55:41Z (GMT). No. of bitstreams: 1 Marcelo Robson de Azevedo Martins da Silva_.pdf: 3067819 bytes, checksum: d7b5c1e064c742114237189fe8cdc3d7 (MD5) Previous issue date: 2017-09-27 / Nenhuma / Existem muitas técnicas para reconstrução de objetos tridimensionais em computador, algumas são empregadas em ambientes controlados e outras em ambientes que não necessitam de grande precisão. Shape From Focus é um método bastante conhecido que utiliza uma pilha de fotografias retiradas com diferentes configurações focais para reconstruir um mapa de profundidade bastante preciso. Este método obtém maior estabilidade na reconstrução de objetos muito pequenos ou microscópios, mas recentemente vem sendo utilizado para reconstrução de ambientes. Com isso, o modelo de reconstrução de mapas de profundidade, Shape From Focus, passou a processar maiores quantidades de interferências na pilha de fotografias, como por exemplo, a distorção da lente, o aumento da profundidade de campo, o efeito zoom, entre outros, e também o ruído introduzido pelo ambiente. Este trabalho analisa os efeitos do suporte adaptativo para o janelamento de avaliação do medidor de qualidade de foco do método Shape From Focus. Apesar de diferentes trabalhos sobre este tema utilizarem diversas variações do janelamento de avaliação, o suporte adaptativo pode fornecer uma alternativa para encontrar a estabilidade e confiança na obtenção do mapa de profundidade, limitando o erro introduzido por interferências globais. / There are many techniques for reconstructing three-dimensional objects in a computer, some are used in controlled environments and others in environments that do not require great precision. Shape From Focus is one of the well-known method that uses a stack of cropped photographs with different focal settings to reconstruct a fairly accurate depth map. This method obtains greater stability in the reconstruction of very small objects or microscopes, but has recently been used for reconstruction of environments. As a result, the Shape From Focus reconstruction model began to process greater amounts of interference in the photo stack, such as lens distortion, increased depth of field, zoom effect, among others, as well as noise Introduced by the environment. This work analyzes the effects of the adaptive support for the evaluation window of the focus quality meter of the Shape From Focus method. Although different works on this theme use several variations of the evaluation window, the adaptive support can provide an alternative to find the stability and confidence in obtaining the depth map, limiting the error introduced by global interferences.
2

From focal stack to light field : Reconstruction of a lightfield

Joujo, Johannes January 2024 (has links)
För att generera ett ljusfält krävs en fokalstack. Fokal stacken kommer att skapas med programvaran Blender. En fokalstack kan ses som mappen som innehåller alla bilderna med olika fokus från en scen. Fokalstack kommer att i denna studie innehålla bilder från samma scen men med olika fokallängeder vilket kommer att göra så att bilderna har olika delar av scenen i fokus. I Blender tillägget ska användaren kunna bestämma hur många bilder som ska skapas och hur fokusdistansen ska skilja sig mellan bilderna. Efter att fokal stacken har skapats kommer den att användas i ljusfältgenereringsalgoritmer för att utvärdera resultatet. Utvärderingen kommer att baseras på tiden det tar att generera ljusfältet och medelvärdet av PSNR. Algoritmerna kommer först att utvärderas individuellt med 35, 41, 50, 60 och 70 fokal stack-bilder. Därefter kommer algoritmerna att jämföras med varandra. Målet med arbetet är att skapa ett Blender-tillägg som möjliggör skapandet av en fokal stack med önskade parametrar, såsom antalet bilder och fokusdistansvariation. Studien har visat att skapandet av ljusfält var effektivare med SART-algoritmerna jämfört med algoritmer som krävde träningsmodelle / A light field requires a focal stack for its generation, and in this study, the focal stack will be created using the software Blender. A focal stack is what the folder containing the different images is called. This study will have the focal stack containing images from a stationary camera with different focal length. Focal length is the parameter deciding what regions is in focus of the scene. An addon will be developed to enable users to create a focal stack from a scene in Blender, allowing them to specify the desired focal length and the number of images. Once the focal stack is generated, it will be utilized in light field generating algorithms to evaluate the time taken to create the light field and the average PSNR value compared to the focal stack. The algorithms will first be evaluated independently with focal stack sizes of 35, 41, 50, 60, and 70 images. Following this, the algorithms will be compared to each other. The study's objective was to create a Blender addon and use the generated focal stacks to assess the performance of light field generation methods. The study demonstrated that light field creation was more effective using the SART algorithms compared to the algorithm requiring model training beforehand.
3

Reading watermarks with a camera phone from printed images

Pramila, A. (Anu) 13 February 2018 (has links)
Abstract There are many reasons for sharing a photo of a printout. The intention might be to copy the image for personal use or experience an interesting ad with friends. With watermarking, the images can also carry side information and with specialized watermarking methods the information can be read with a mobile device camera. In digital image watermarking, information is hidden on an image in such a way that a computer can read the hidden information but a human cannot discern it. The aim of this thesis is to research the process in which the watermarked image is printed and then read with a digital camera or a camera phone from the printed image. In order to survive the process, the watermark must survive multiple attacks. Some of the attacks occur during printing as the image is halftoned, others when the image is recaptured with a camera, in which case the camera might be rotated around multiple axis. These attacks may cause a loss of synchronization of the watermark and make the extraction impossible. The main objective of the thesis is thus to develop methods that are robust to the printing and capturing process, especially for the situations when the capturing angle is large. This problem contains the circumstances in which the synchronization is lost and the camera lens is not focused properly. In this work, research on digital image watermarking, computational photography and mobile phones are combined. The contributions of this thesis lie in two main parts: First, two print-cam robust methods are proposed, one based on a frame and the other on autocorrelation for synchronization. These two are then used as a basis for an algorithm that recovers the watermark even after camera rotation and image blurring caused by the narrow depth of focus of the lens. The algorithm is later refined and implemented for a mobile phone. The results show that the method is highly robust to capturing the watermark without errors in angles up to 60° with processing times acceptable for real-life applications. / Tiivistelmä On olemassa useita syitä tulosteesta otetun valokuvan jakamiseen. Aikomuksena voi olla kopioida kuva omaan käyttöön tai jakaa mielenkiintoinen ilmoitus ystävien kanssa. Vesileimauksessa kuvaan voidaan sijoittaa lisätietoa ja erityisillä menetelmillä tieto voidaan myöhemmin lukea mobiililaitteen kameralla. Digitaalisten kuvien vesileimauksen tavoite on piilottaa tietoa kuvaan siten, että tietokone pystyy lukemaan piilotetun informaation, siinä missä ihminen ei pysty sitä havaitsemaan. Tämän väitöskirjan tavoitteena on tutkia prosessia, missä vesileimattu kuva tulostetaan ja vesileima luetaan digitaalisella kameralla tai kamerapuhelimella tulosteesta. Selviytyäkseen tästä prosessista, vesileiman on kestettävä useita hyökkäyksiä. Osa hyökkäyksistä esiintyy tulostuksen aikana, kun kuva rasteroidaan, ja osa valokuvatessa, jolloin kamera voi olla kiertynyt. Näiden hyökkäysten seurauksena vesileiman synkronointi voi kadota, jolloin vesileiman lukeminen ei enää onnistu. Väitöskirjan päätavoitteena on siis kehittää tulostuksen ja valokuvauksen kestäviä vesileimausmenetelmiä erityisesti niitä tilanteita varten, jolloin kuvauskulma on suuri. Tämä ongelma sisältää olosuhteet, joissa synkronointi menetetään, ja kun kameran linssi ei ole kohdistunut oikein. Työssä yhdistetään digitaalinen kuvien vesileimaus, laskennallinen valokuvaus ja matkapuhelimet. Tutkimus voidaan jakaa kahteen osa-alueeseen: Ensimmäisessä kehitetään kaksi tulostuksen ja valokuvauksen kestävää menetelmää, joista toinen perustuu kehykseen ja toinen autokorrelaatioon synkronoinnin säilyttämiseksi. Toisessa osassa näitä menetelmiä hyödynnetään algoritmissa, joka kykenee vesileiman lukemiseen myös silloin kun kameran kiertyminen on voimakasta ja objektiivin kapea tarkennussyvyys aiheuttaa sumeita alueita kuvassa. Tutkimustyön lopussa tätä algoritmia viedään eteenpäin ja testataan matkapuhelinalustalla. Tulokset osoittavat menetelmän kestävän kameran kiertymistä 60°:seen saakka suoritusajoilla, jotka ovat hyväksyttäviä sovelluskäyttöön.

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