Robust Techniques for Feature-based Image Mosaicing

Since the last few decades, image mosaicing in real time applications has been a challenging field for image processing experts. It has wide applications in the field of video conferencing, 3D image reconstruction, satellite imaging and several medical as well as computer vision fields. It can also be used for mosaic-based localization, motion detection & tracking, augmented reality, resolution enhancement, generating large FOV etc. In this research work, feature based image mosaicing technique using image fusion have been proposed. The image mosaicing algorithms can be categorized into two broad horizons. The first is the direct method and the second one is based on image features. The direct methods need an ambient initialization whereas, Feature based methods does not require initialization during registration. The feature-based techniques are primarily followed by the four steps: feature detection, feature matching, transformation model estimation, image resampling and transformation. SIFT and SURF are such algorithms which are based on the feature detection for the accomplishment of image mosaicing, but both the algorithms has their own limitations as well as advantages according to the applications concerned. The proposed method employs this two feature based image mosaicing techniques to generate an output image that works out the limitations of the both in terms of image quality The developed robust algorithm takes care of the combined effect of rotation, illumination, noise variation and other minor variation. Initially, the input images are stitched together using the popular stitching algorithms i.e. Scale Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF). To extract the best features from the stitching results, the blending process is done by means of Discrete Wavelet Transform (DWT) using the maximum selection rule for both approximate as well as detail-components

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

Image mosaicing based condition monitoring approach for multi robots at production lines in industrial autonomy systems

In today industry, manufacturing become big and serial as it never been before thanks to the autonomy robots. Hitches on such autonomy systems used in industrial production may cause production delaying. In this study, it is aimed to obtain alive bird's eye view map of full system in order to monitor manufacturing robots at production facilities that are big and impossible to be monitored with only one camera. Finding the similar scenes of input images, estimation of homography, warping and blending operations are applied respectively in order to mosaic the images by twos. Thus the robots in the facility can be observed in one screen. With observation of the obtained images, faults on cyber-physical systems that may cause damage in machines which are not cheap can be handled beforetime

Image Mosaicing and Producing a Panoramic Visibility

Aim of this research paper is to take multiple input images , the input images are having some of the overlapped region with one another. Since digital cameras cant take photos of a wider view, for a wider view we need a highly sophisticated camera. It is therefore being attempted to develop enabling methodology which can convert the corresponding images captured form such cameras into a panoramic view. In this paper a n algorithm is used and applied some of the advanced function available in matlab to make this work much more efficient

Image Mosaicing for Wide Angle Panorama

Images are integral part in our daily lives. With a normal camera it is not possible to get a wide angle panorama with high resolution. Image Mosaicing is one of the novel techniques, for combining two or more images of the same scene taken in different views into one image. In the dark areas, the obtained image is a panoramic image with high resolution without mask. But in the case of lighting areas, the resultant image is generating mask. In order to gets wide angle panorama, in the existing system, extracting feature points, finding the best stitching line, Cluster Analysis (CA) and Dynamic Programming (DP) methods are used. Also used Weighted Average (WA) method for smooth stitching results and also eliminate intensity seam effectively. In the proposed system, to get feature extraction and feature matching SIFT (Scaled Invariant Feature Transform) algorithm used. In this process, outliers can be generated. RANSAC (Random Sample Consensus) is used for detecting the outliers from the resultant image. Masking is significantly reduced by using Algebraic Reconstruction Techniques (ART)

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

SIMULASI DAN ANALISIS CITRA MOSAIK BERBASIS FITUR DENGAN METODE GLOBAL ALIGNMENT UNTUK PEMBENTUKAN CITRA PANORAMA

ABSTRAKSI: Perkembangan bidang fotografi kini semakin meningkat sejak ditemukannya kamera digital. Namun sampai sekarang belum ditemukan solusi yang optimal dengan biaya yang rendah untuk mengambil citra dengan sudut pandang yang lebar, yang disebut citra panorama. Untuk mengatasi permasalahan tersebut, dapat digunakan proses penggabungan citra yang saling overlap atau sering disebut dengan citra mosaik.Pada perancangan citra mosaik di dalam tugas akhir ini terdiri dari beberapa proses, yaitu: input citra, preprocessing, global alignment method, homography projection, dan image compositing. Input sistem adalah 2 buah citra yang saling overlap, yang merupakan bagian dari objek citra panorama yang utuh. Pada proses preprocessing dilakukan proses normalisasi citra dan pengabuan citra (grayscaling). Tahap selanjutnya adalah penerapan metode global alignment, untuk menemukan parameter pendaftaran gambar yang terbaik sesuai dengan kendala diberikan oleh penyesuaian gambar. Dengan metode ini, peran user hanya meng-input-kan 2 citra saja, dan selanjutnya sistem akan mencari ciri dan proses-proses lainnya secara otomatis. Lalu dengan homography projection citra kedua diubah proyeksinya agar menyerupai citra pertama. Terakhir setelah dilakukan berbagai proses pada tahap sebelumnya, kedua citra input akan di komposisi, atau digabungkan menjadi sebuah citra panorama yang utuh. Keunggulan dari metode ini yaitu tidak lagi terlihat kesenjangan dan sambungan gambar pada hasil penggabungan citra mosaik karena dapat meminimalisasi error yang terjadi. Selain itu metode ini memiliki keunggulan dapat menggabungkan lebih dari 2 citra dan dapat mengabungkan citra dengan orientasi horizontal maupun vertikal.Dalam penelitian ini telah dihasilkan sebuah simulasi citra mosaik yang tak tampak sambungan gambarnya dalam penggabungan dua buah citra yang saling overlap dengan nilai rata-rata MSE yang dihasilkan sebesar 0.0021, nilai rata-rata PSNR yang dihasilkan sebesar 77.22 dB, dan nilai rata-rata korelasi yang dihasilkan sebesar 0.98. Sekaligus dapat mengurangi error rata-rata sebesar 0.167 piksel dengan waktu komputasi rata-rata sebesar 263,158 detik.Kata Kunci : citra panorama, citra mosaik, global alignmentABSTRACT: The development of photography now has increased since the introduction of digital cameras. But until now it has not found the optimal solution at a low cost to take images with a wide viewing angle, called the panoramic image. To overcome these problems, it can be used the process of merging the overlapping images or we can called image mosaic.In designing an image mosaic in this thesis consists of several processes, namely: input image, preprocessing, global alignment method, homography projection, and image compositing. Input image is 2 pieces of overlapping image, which is part of the whole panorama image object. In the process of image preprocessing performed normalization process and grayscaling image. The next stage is the implementation of a global alignment method, to find the best parameter of image registration according to the constraints given by the image adjustment. With this method, the user only to input 2 image, and then the system will search for the feature and other processes automatically. Then with the homography projection the second image changed it’s projection to resemble into the first image. Recently after the various processes in the previous stage, both of input image will be merged, or combined into a panoramic image. The advantage of this method is no longer visible gaps and on the result of image mosaic and then can build seamless image mosaic because it can minimize the errors that occurred. Beside that, this method can merge more than two image and then can merge image with horizontal and vertical orientation.In this research has generated a simulated seamless aligned image mosaic in merging two overlapping images with the average result value of MSE is 0.0021, the average result value of PSNR is 77.22 dB, and the average result value of correlation is 0.98. And simultaneously can reduce the average error value are 0.167 pixel with an average computation time of 263.158 seconds.Keyword: panoramic image, image mosaic, global alignmen

IMPLEMENTASI DAN ANALISIS CITRA MOSAIK BERBASIS FITUR DENGAN METODE GLOBAL ALIGNMENT UNTUK PEMBENTUKAN CITRA PANORAMA PADA ANDROID

ABSTRAKSI: Pengolahan citra digital semakin berkembang dari waktu ke waktu. Perkembangan pengolahan citra digital dapat menjadi solusi yang melengkapi keterbatasan-keterbatasan dalam bidang fotografi, diantaranya keterbatasan untuk mengambil citra dengan sudut pandang yang lebar atau sering disebut citra panorama. Sedangkan perkembangan teknologi membuat handphone yang dahulu digunakan hanya untuk bertelepon atau mengirimkan pesan, menjadi ‘telepon pintar’ yang terintegrasi dan bisa melakukan berbagai fungsi dari perangkat elektronik lain, misalnya kamera. Ditambah oleh hadirnya platform Android sebagai sistem oprasi mobile dengan sifatnya yang open source, sehingga memungkinkan para developer untuk membuat dan mengembangkan aplikasi sesuai dengan kebutuhan. Berangkat dari dua hal tersebut, maka dalam tugas akhir ini akan dirancang sebuah aplikasi berbasis Android yang menjadi solusi dari pengambilan gambar panorama dari kamera biasa, menggunakan dua buah gambar yang saling tumpang tindih atau disebut citra mosaik. Aplikasi ini akan dibuat menggunakan Global Alignment Method yang merupakan pengembangan dari metode-metode sebelumnya. Untuk ekstraksi fitur digunakan metode SURF, untuk fitur match digunakan algoritma Greedy, untuk mengeliminasi outlier digunakan RANSAC, lalu terakhir dilakukan pemetaan citra input kedua pada citra input pertama dengan menggunakan matriks yang diperoleh dari hasil homography mapping. Input dari aplikasi ini bisa terdiri dari dua macam: pengguna mengambil gambar langsung dari kamera, atau pengguna mengambil gambar yang telah ditangkap sebelumnya dan tersimpan di dalam galeri. Dari implementasi ini dihasilkan aplikasi yang dapat menghasilkan citra panorama dengan rata-rata waktu komputasi 7.7s untuk input galeri, dan 8.7s untuk input kamera, rata-rata MSE 0.0145, dan rata-rata nilai korelasi 0.8594, serta daerah overlap optimal 25%.Kata Kunci : Image Mosaicking, Global Alignment Method, SURF, Greedy, RANSAC, Android.ABSTRACT: Digital image processing is growing from time to time . The development of digital image processing can be a solution that complements the limitations in the photography field, including limitations to take images with a wide viewing angle, or often called a panoramic image . While the development of technology makes mobile phones were used only for the phone or send a message, to be a \u27smart phones\u27 that integrated and can perform a variety of functions from other electronic devices, such as cameras. Coupled by the presence of the Android platform as a mobile operating system with its open source, allowing developers create and develop applications according to their own needs. Based on these two things, then the final project will be designed as an Android-based application that can be the solution of panoramic maker from camera, using two overlapping images that called mosaic images. This application will be made using Global Image Method which is an enhance from previous methods . For feature extraction, SURF is used, to match the features used Greedy Algorithm, RANSAC is used to eliminate outliers, and the last one is mapping the second input image to the first input image using a matrix obtained from the homographic mapping. Input from the application can be composed of two kinds: user takes a picture directly from the camera, or user takes a picture that had been previously captured and stored in the gallery. From this implementation, created an application that can create panoramic image with the average of computation time is 7.7s for gallery input, and 8.7 for camera input, the average of MSE is 0.0145, and the average of correlation value is 0.08594, and the optimum overlap region is 25%.Keyword: Image Mosaicking, Global Alignment Method, SURF, Greedy, RANSAC, Android

Image Mosaicing Using Feature Detection Algorithms

In most recent couple of decades, image processing specialists has been using image mosaicing as a testing field in real time applications. It has wide utilization in the 3D picture reproduction, field of satellite imaging, computer vision fields and a few therapeutic fields also. Movement recognition & tracking, mosaic-based localisation, resolution enhancement, generating substantial FOV, augmented reality, and so forth are also some of its application fields. In this exploration work, feature based image mosaicing procedure has been proposed. There are five essential steps in feature based procedures: feature extraction, feature matching, transformation model estimation, image re-sampling and transformation, and image blending. The achievement of image mosaicing can be accounted by the feature identification algorithms such as Harris corner detector, SURF, FAST and FREAK. But each of these algorithms has their own particular impediments and preferences as indicated by the applications concerned. The proposed strategy first compares the above mentioned four feature extraction algorithm on the basis of accuracy and computational time and determines FREAK to be the most optimum one and then utilizes this FREAK descriptor algorithm for feature detection. All the distinctive features detected in an image and the feature descriptors are shaped around the corners. Matching between the feature descriptors from both the images is done to achieve best closeness and all the features other than the ones with higher degree of resemblance are rejected. Now, the features with higher degree of resemblance are used for computing the transformation model and correspondingly, the warping of the image is done. The warping of the picture is done on a typical mosaic plane after estimation. The removal of the intensity seam in the neighbourhood of the boundary of the images and to modify the image grey levels at the junction joint to obtain a smooth transition between the images is the final step. Alpha blending technique is utilized for the purpose of image blendin