Research on Image Mosaic based on SIFT

图像拼接就是把针对同一场景的相互有部分重叠的一系列图片合成一幅大的宽视角的图像．拼接后的图像要求最大程度地与原始图像接近，失真尽可能小。 图像拼接技术在宇宙空间探测、海底勘测、医学、气象、地质勘测、军事、视频压缩和传输，档案的数字化保存，视频的索引和检索，3D重建，军事侦察和公安取证，超分辨复原等领域都有广泛的应用．主要表现为： l、全景图和超宽视角图像的合成：将普通图像或视频图像进行无缝拼接，得到超宽视角甚至360°的全景图，这样就可以用普通相机实现全景的拍摄； 2、碎片图像的组合：将医学和科研的显微碎片图像或者空间、海底探测得到的局部图像合成大幅的整体图像； 3、虚拟现实：图像拼接...Image mosaic is to compose a large and full view picture with two pictures that have partly overlapped. The final composed pictures must be conforming to originally picture. The distortion should be as little as possible. Image mosaic was used for space exploration, underwater survey, medicine, meteorology and geological survey. Mainly for: 1, Panorama and full view picture composed: We can us...学位：工程硕士院系专业：信息科学与技术学院通信工程系_电子与通信工程学号：X200622403

Template Matching Method for Recognition of Stone Inscripted Kannada Characters of Different Time Frames Based on Correlation Analysis

Stone inscripted literature speaks about the history, language of different regions of the world. Preservation of such document through digitalization process is become very important. To stop degradation and missing further, the analysis of the same will through light on historical events of that region. In this connection present work proposes a simple method of digitization using ordinary digital camera further, the pre-processing algorithm is implemented to enhance the image and improve the readability. Here it recognizes the Kannada characters based on template matching. In this method is normally implemented by first picking template and then it  call the search image, then by simply comparing the  template over each point in the search image and it calculate the sum of products between the coefficient. Based on this calculated product value it recognizes the character.  Cross correlation technique is implemented in matching the characters coefficient. Experimental results shows, it demonstrates relatively high accuracy in recognizing Stone inscriptions characters of both Hoysala, Ganga time frames and with better time efficiency when compared to previous methods. DOI:http://dx.doi.org/10.11591/ijece.v4i5.633

Performance analysis on color image mosaicing techniques on FPGA

Today, the surveillance systems and other monitoring systems are considering the capturing of image sequences in a single frame. The captured images can be combined to get the mosaiced image or combined image sequence. But the captured image may have quality issues like brightness issue, alignment issue (correlation issue), resolution issue, manual image registration issue etc. The existing technique like cross correlation can offer better image mosaicing but faces brightness issue in mosaicing. Thus, this paper introduces two different methods for mosaicing i.e., (a) Sliding Window Module (SWM) based Color Image Mosaicing (CIM) and (b) Discrete Cosine Transform (DCT) based CIM on Field Programmable Gate Array (FPGA). The SWM based CIM adopted for corner detection of two images and perform the automatic image registration while DCT based CIM aligns both the local as well as global alignment of images by using phase correlation approach. Finally, these two methods performances are analyzed by comparing with parameters like PSNR, MSE, device utilization and execution time. From the analysis it is concluded that the DCT based CIM can offers significant results than SWM based CIM

An in Depth Review Paper on Numerous Image Mosaicing Approaches and Techniques

Image mosaicing is one of the most important subjects of research in computer vision at current. Image mocaicing requires the integration of direct techniques and feature based techniques. Direct techniques are found to be very useful for mosaicing large overlapping regions, small translations and rotations while feature based techniques are useful for small overlapping regions. Feature based image mosaicing is a combination of corner detection, corner matching, motion parameters estimation and image stitching.Furthermore, image mosaicing is considered the process of obtaining a wider field-of-view of a scene from a sequence of partial views, which has been an attractive research area because of its wide range of applications, including motion detection, resolution enhancement, monitoring global land usage, and medical imaging. Numerous algorithms for image mosaicing have been proposed over the last two decades.In this paper the authors present a review on different approaches for image mosaicing and the literature over the past few years in the field of image masaicing methodologies. The authors take an overview on the various methods for image mosaicing.This review paper also provides an in depth survey of the existing image mosaicing algorithms by classifying them into several groups. For each group, the fundamental concepts are first clearly explained. Finally this paper also reviews and discusses the strength and weaknesses of all the mosaicing groups

A Comparative Analysis of Feature Detection and Matching Algorithms for Aerial Image Stitching

Features detection and matching are the essential processes in image mosaicing and computer vision applications. Our work intend to find descriptors that are obtained by considering all interest/feature points and its locations on images, and then form a set of corresponding spatial relations based on the interest points between images. Hence in this paper, we will evaluate and present the performance of a few detectordescriptor-matcher approaches on raw aerial images for stitching image purposes. We have experimented on Canny Edge Detector, SIFT and SURF approaches to extract feature points. The extracted descriptors are then matched using FLANN based matcher. Finally, the RANSAC Homography is used to estimate the transformation model so stitching procedure could be applied in order to produce a mosaic aerial image. The results have shown that SURF approach outperforms the others in terms of its robustness of the method and higher speed in execution time

Development Of A High Performance Mosaicing And Super-Resolution Algorithm

In this dissertation, a high-performance mosaicing and super-resolution algorithm is described. The scale invariant feature transform (SIFT)-based mosaicing algorithm builds an initial mosaic which is iteratively updated by the robust super resolution algorithm to achieve the final high-resolution mosaic. Two different types of datasets are used for testing: high altitude balloon data and unmanned aerial vehicle data. To evaluate our algorithm, five performance metrics are employed: mean square error, peak signal to noise ratio, singular value decomposition, slope of reciprocal singular value curve, and cumulative probability of blur detection. Extensive testing shows that the proposed algorithm is effective in improving the captured aerial data and the performance metrics are accurate in quantifying the evaluation of the algorithm

Desarrollo de un aplicativo para la generación de mosaicos 2d enfocado al seguimiento de infraestructuras lineales de transporte de energía

En este proyecto se evalúo una serie de detectores y descriptores con el propósito de determinar las combinaciones con mejor desempeño en cuanto a tiempo y precisión, para la generación de mosaicos de imágenes. Adicionalmente se implementó un algoritmo para buscar la correspondencia entre imágenes contiguas, para la obtención del modelo de transformación, en la generación del mosaico. El proceso de este estudio se llevó a cabo a través de cinco (5) fases, Investigación, Elaboración de Base de Datos, Validación, Búsqueda de Correspondencias y Desarrollo del Prototipo.In this project a series of detectors and descriptors for the purpose of determining the best performing combinations were evaluated in terms of time and precision, for generating image mosaicing. Additionally, an algorithm is implemented to search for the correspondence between adjacent images, to obtain the transformation model, the generation of the mosaic. The process of this study was performed through five (5) phases, Research, Database Elaboration, Validation, Search Correspondence and Prototype Development.Pregrad

An Image Based Vibration Sensor for Soft Tissue Modal Analysis in a Digital Image Elasto Tomography (DIET) System

Digital Image Elasto Tomography (DIET) is a non-invasive elastographic breast cancer screening technology, relying on image-based measurement of surface vibrations induced on a breast by mechanical actuation. Knowledge of frequency response characteristics of a breast prior to imaging is critical to maximize the imaging signal and diagnostic capability of the system. A non-invasive image based modal analysis system that is designed to be able to robustly and rapidly identify resonant frequencies in soft tissue is presented in this thesis. A feasibility analysis reveals that three images per oscillation cycle are sufficient to capture the relative motion behavior at a given frequency. Moreover, the analysis suggests that 2D motion analysis is able to give an accurate estimation of the response at a particular frequency. Thus, a sweep over critical frequency ranges can be performed prior to imaging to determine critical imaging settings of the DIET system to maximize diagnositc performance. Based on feasibility simulations, a modal analysis system is presented that is based on the existing DIET digital imaging system. A frequency spectrum plot that comprises responses gathered from more than 30 different frequencies can be obtained in about 6 minutes. Preliminary results obtained from both phantom and human trials indicate that distinctive resonant frequencies can be obtained with the modal analysis system. Due to inhomogeneous properties of human breast tissues, different imaging location appear to pick up different resonances. However, there has been very limited clinical data for validating such behavior. Overall, a modal analysis system for soft tissue has been developed in this thesis. The system was first evaluated in simulation, then implemented in hardware and software, and finally successfully validated in silicone phantoms as well as human breasts