Search results for: image processing of Electrical impedance tomography.

Authors: Ayman A. AbuBaker, Rami S.Qahwaji, Musbah J. Aqel, Mohmmad H. Saleh

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Two algorithms are proposed to reduce the storage requirements for mammogram images. The input image goes through a shrinking process that converts the 16-bit images to 8-bits by using pixel-depth conversion algorithm followed by enhancement process. The performance of the algorithms is evaluated objectively and subjectively. A 50% reduction in size is obtained with no loss of significant data at the breast region.

Keywords: Breast cancer, Image processing, Image reduction, Mammograms, Image enhancement

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Authors: Madhuri Khambete, Madhuri Joshi

Abstract:

Quality evaluation of an image is an important task in image processing applications. In case of image compression, quality of decompressed image is also the criterion for evaluation of given coding scheme. In the process of compression -decompression various artifacts such as blocking artifacts, blur artifact, ringing or edge artifact are observed. However quantification of these artifacts is a difficult task. We propose here novel method to quantify blur and ringing artifact in an image.

Keywords: Blur, Compression, Objective Quality assessment, Ringing artifact.

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Authors: V. Pérez-Herranz, M. Pinel, E. M. Ortega, M. García-Gabaldón

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In the present work, Electrochemical Impedance Spectrocopy (EIS) is applied to study the transport of different metal cations through a cation-exchange membrane. This technique enables the identification of the ionic-transport characteristics and to distinguish between different transport mechanisms occurring at different current density ranges. The impedance spectra are dependent on the applied dc current density, on the type of cation and on the concentration. When the applied dc current density increases, the diameter of the impedance spectra loops increases because all the components of membrane system resistance increase. The diameter of the impedance plots decreases in the order of Na(I), Ni(II) and Cr(III) due to the increased interactions between the negatively charged sulfonic groups of the membrane and the cations with greater charge. Nyquist plots are shifted towards lower values of the real impedance, and its diameter decreases with the increase of concentration due to the decrease of the solution resistance.

Keywords: Ion-exchange Membranes, Electrochemical Impedance Espectroscopy, Multivalent Metal Cations.

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Authors: S.K. Satpathy, S.K. Nayak, K. K. Nagwanshi, S. Panda, C. Ardil

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Image restoration involves elimination of noise. Filtering techniques were adopted so far to restore images since last five decades. In this paper, we consider the problem of image restoration degraded by a blur function and corrupted by random noise. A method for reducing additive noise in images by explicit analysis of local image statistics is introduced and compared to other noise reduction methods. The proposed method, which makes use of an a priori noise model, has been evaluated on various types of images. Bayesian based algorithms and technique of image processing have been described and substantiated with experimentation using MATLAB.

Keywords: Image Restoration, Probability DensityFunction (PDF), Neural Networks, Bayesian Classifier.

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Authors: Somnath Dey, Debasis Samanta

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Iris-based biometric system is gaining its importance in several applications. However, processing of iris biometric is a challenging and time consuming task. Detection of iris part in an eye image poses a number of challenges such as, inferior image quality, occlusion of eyelids and eyelashes etc. Due to these problems it is not possible to achieve 100% accuracy rate in any iris-based biometric authentication systems. Further, iris detection is a computationally intensive task in the overall iris biometric processing. In this paper, we address these two problems and propose a technique to localize iris part efficiently and accurately. We propose scaling and color level transform followed by thresholding, finding pupil boundary points for pupil boundary detection and dilation, thresholding, vertical edge detection and removal of unnecessary edges present in the eye images for iris boundary detection. Scaling reduces the search space significantly and intensity level transform is helpful for image thresholding. Experimental results show that our approach is comparable with the existing approaches. Following our approach it is possible to detect iris part with 95-99% accuracy as substantiated by our experiments on CASIA Ver-3.0, ICE 2005, UBIRIS, Bath and MMU iris image databases.

Keywords: Iris recognition, iris localization, biometrics, image processing.

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Authors: HaeNa Lee, Sun K. Yoo

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Volume rendering is widely used in medical CT image visualization. Applying 3D image visualization to diagnosis application can require accurate volume rendering with high resolution. Interpolation is important in medical image processing applications such as image compression or volume resampling. However, it can distort the original image data because of edge blurring or blocking effects when image enhancement procedures were applied. In this paper, we proposed adaptive tension control method exploiting gradient information to achieve high resolution medical image enhancement in volume visualization, where restored images are similar to original images as much as possible. The experimental results show that the proposed method can improve image quality associated with the adaptive tension control efficacy.

Keywords: Tension control, Interpolation, Ray-casting, Medical imaging analysis.

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Authors: Yoshiaki Takeda, Norifumi Aoyama, Takahiro Tanaami, Syouhei Honda, Kenta Tabata, Hiroyuki Kamata

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In this paper, we validate crater detection in moon surface image using FLDA. This proposal assumes that it is applied to SLIM (Smart Lander for Investigating Moon) project aiming at the pin-point landing to the moon surface. The point where the lander should land is judged by the position relations of the craters obtained via camera, so the real-time image processing becomes important element. Besides, in the SLIM project, 400kg-class lander is assumed, therefore, high-performance computers for image processing cannot be equipped. We are studying various crater detection methods such as Haar-Like features, LBP, and PCA. And we think these methods are appropriate to the project, however, to identify the unlearned images obtained by actual is insufficient. In this paper, we examine the crater detection using FLDA, and compare with the conventional methods.

Keywords: Crater Detection, Fisher Linear Discriminant Analysis , Haar-Like Feature, Image Processing.

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Authors: Kedit J.

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This paper is the tomographic images reconstruction simulation for defects detection in specimen. The specimen is the thin cylindrical steel contained with low density materials. The defects in material are simulated in three shapes.The specimen image function will be transformed to projection data. Radon transform and its inverse provide the mathematical for reconstructing tomographic images from projection data. The result of the simulation show that the reconstruction images is complete for defect detection.

Keywords: Tomography, Tomography Reconstruction, Radon Transform

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Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

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Real time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Thus, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Edge detection is one of the basic building blocks of video and image processing applications. It is a common block in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: High Level Synthesis, Canny edge detection, Hardware accelerators, and Computer Vision.

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Authors: Yee Yee Htun, Dr. Khaing Khaing Aye

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Morphological operators transform the original image into another image through the interaction with the other image of certain shape and size which is known as the structure element. Mathematical morphology provides a systematic approach to analyze the geometric characteristics of signals or images, and has been applied widely too many applications such as edge detection, objection segmentation, noise suppression and so on. Fuzzy Mathematical Morphology aims to extend the binary morphological operators to grey-level images. In order to define the basic morphological operations such as fuzzy erosion, dilation, opening and closing, a general method based upon fuzzy implication and inclusion grade operators is introduced. The fuzzy morphological operations extend the ordinary morphological operations by using fuzzy sets where for fuzzy sets, the union operation is replaced by a maximum operation, and the intersection operation is replaced by a minimum operation. In this work, it consists of two articles. In the first one, fuzzy set theory, fuzzy Mathematical morphology which is based on fuzzy logic and fuzzy set theory; fuzzy Mathematical operations and their properties will be studied in details. As a second part, the application of fuzziness in Mathematical morphology in practical work such as image processing will be discussed with the illustration problems.

Keywords: Binary Morphological, Fuzzy sets, Grayscalemorphology, Image processing, Mathematical morphology.

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Authors: Chalakorn Chitsaart, Suchada Rianmora, Noppawat Vongpiyasatit

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In order to reduce the transportation time and cost for direct interface between customer and manufacturer, the image processing technique has been introduced in this research where designing part and defining manufacturing process can be performed quickly. A3D virtual model is directly generated from a series of multi-view images of an object, and it can be modified, analyzed, and improved the structure, or function for the further implementations, such as computer-aided manufacturing (CAM). To estimate and quote the production cost, the user-friendly platform has been developed in this research where the appropriate manufacturing parameters and process detections have been identified and planned by CAM simulation.

Keywords: Image processing technique, Feature detections, Surface registrations, Capturing multi-view images, Production costs, and Manufacturing processes.

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life due to the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or COVID-19 induced pneumonia. The early prediction and classification of such lung diseases help reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans are pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publicly available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scans, COVID-19, deep learning, image processing, pneumonia, lung disease.

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Authors: N. Z. Azlan, H. Yamaura

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This paper presents the Function Approximation Technique (FAT) based adaptive impedance control for a robotic finger. The force based impedance control is developed so that the robotic finger tracks the desired force while following the reference position trajectory, under unknown environment position and uncertainties in finger parameters. The control strategy is divided into two phases, which are the free and contact phases. Force error feedback is utilized in updating the uncertain environment position during contact phase. Computer simulations results are presented to demonstrate the effectiveness of the proposed technique.

Keywords: Adaptive impedance control, force based impedance control, force control, Function Approximation Technique (FAT), unknown environment position.

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Authors: Zheng Zhang, Xin Chen, Guoqing Ding

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Electronic apex locators (EAL) has been widely used clinically for measuring root canal working length with high accuracy, which is crucial for successful endodontic treatment. In order to maintain high accuracy in different measurement environments, this study presented a system for root canal length measurement based on multifrequency impedance method. This measuring system can generate a sweep current with frequencies from 100 Hz to 1 MHz through a direct digital synthesizer. Multiple impedance ratios with different combinations of frequencies were obtained and transmitted by an analog-to-digital converter and several of them with representatives will be selected after data process. The system analyzed the functional relationship between these impedance ratios and the distance between the file and the apex with statistics by measuring plenty of teeth. The position of the apical foramen can be determined by the statistical model using these impedance ratios. The experimental results revealed that the accuracy of the system based on multifrequency impedance ratios method to determine the position of the apical foramen was higher than the dual-frequency impedance ratio method. Besides that, for more complex measurement environments, the performance of the system was more stable.

Keywords: Root canal length, apex locator, multifrequency impedance, sweep frequency.

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Authors: Fathi M. O. Hamed, Salma F. Elkofhaifee

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The aim of this work is to detect geometrical shape objects in an image. In this paper, the object is considered to be as a circle shape. The identification requires find three characteristics, which are number, size, and location of the object. To achieve the goal of this work, this paper presents an algorithm that combines from some of statistical approaches and image analysis techniques. This algorithm has been implemented to arrive at the major objectives in this paper. The algorithm has been evaluated by using simulated data, and yields good results, and then it has been applied to real data.

Keywords: Image processing, median filter, projection, scalespace, segmentation, threshold.

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Authors: Ahd Aljarf, Saad Amin

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Images are important source of information used as evidence during any investigation process. Their clarity and accuracy is essential and of the utmost importance for any investigation. Images are vulnerable to losing blocks and having noise added to them either after alteration or when the image was taken initially, therefore, having a high performance image processing system and it is implementation is very important in a forensic point of view. This paper focuses on improving the quality of the forensic images. For different reasons packets that store data can be affected, harmed or even lost because of noise. For example, sending the image through a wireless channel can cause loss of bits. These types of errors might give difficulties generally for the visual display quality of the forensic images. Two of the images problems: noise and losing blocks are covered. However, information which gets transmitted through any way of communication may suffer alteration from its original state or even lose important data due to the channel noise. Therefore, a developed system is introduced to improve the quality and clarity of the forensic images.

Keywords: Image Filtering, Image Reconstruction, Image Processing, Forensic Images.

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Authors: Sri Hartati, 1Agus Harjoko, Brad G. Nickerson

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A prototype of an anomaly detection system was developed to automate process of recognizing an anomaly of roentgen image by utilizing fuzzy histogram hyperbolization image enhancement and back propagation artificial neural network. The system consists of image acquisition, pre-processor, feature extractor, response selector and output. Fuzzy Histogram Hyperbolization is chosen to improve the quality of the roentgen image. The fuzzy histogram hyperbolization steps consist of fuzzyfication, modification of values of membership functions and defuzzyfication. Image features are extracted after the the quality of the image is improved. The extracted image features are input to the artificial neural network for detecting anomaly. The number of nodes in the proposed ANN layers was made small. Experimental results indicate that the fuzzy histogram hyperbolization method can be used to improve the quality of the image. The system is capable to detect the anomaly in the roentgen image.

Keywords: Image processing, artificial neural network, anomaly detection.

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Authors: Shobha Sharma, Amita Dev, Akanksha Kant

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Digital signal processor, image signal processor and FIR filters have multipliers as an important part of their design. On the basis of Vedic mathematics, Vedic multipliers have come out to be very fast multipliers. One of the image processing applications is edge detection. This research presents a small area and high speed 8 bit Vedic multiplier system comprising of compressor based adders. This results in faster edge detection. This architecture is tested on Xilinx vertex 4 FPGA board and simulations were carried out using the Xilinx synthesis tool. Comparisons are made and this system is found to be smaller in area with high speed (the lesser propagation delay). This compressor based Vedic multiplier is 1.1 times speedier than a typical Vedic multiplier. Also, this Vedic Multiplier is 2 times speedier than a ‘simple’ multiplier.

Keywords: Detection of edges, Vedic multiplier, image processing, Urdhva Tiryakbhyam sutra.

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Authors: Aicha Baya Goumeidane, Nafaa. Nacereddine

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A welded structure must be inspected to guarantee that the weld quality meets the design requirements to assure safety and reliability. However, X-ray image analyses and defect recognition with the computer vision techniques are very complex. Most difficulties lie in finding the small, irregular defects in poor contrast images which requires pre processing to image, extract, and classify features from strong background noise. This paper addresses the issue of designing methodology to extract defect from noisy background radiograph with image processing. Based on the use of actives contours this methodology seems to give good results

Keywords: Welding, Radiography, Computer vision, Active contour.

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Authors: Madina Hamiane, Amina Khunji

Abstract:

Detecting changes in multiple images of the same scene has recently seen increased interest due to the many contemporary applications including smart security systems, smart homes, remote sensing, surveillance, medical diagnosis, weather forecasting, speed and distance measurement, post-disaster forensics and much more. These applications differ in the scale, nature, and speed of change. This paper presents an application of image processing techniques to implement a real-time change detection system. Change is identified by comparing the RGB representation of two consecutive frames captured in real-time. The detection threshold can be controlled to account for various luminance levels. The comparison result is passed through a filter before decision making to reduce false positives, especially at lower luminance conditions. The system is implemented with a MATLAB Graphical User interface with several controls to manage its operation and performance.

Keywords: Image change detection, Image processing, image filtering, thresholding, B/W quantization.

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Authors: Wan Nural Jawahir Wan Yussof, Hans Burkhardt

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Liver segmentation is the first significant process for liver diagnosis of the Computed Tomography. It segments the liver structure from other abdominal organs. Sophisticated filtering techniques are indispensable for a proper segmentation. In this paper, we employ a 3D anisotropic diffusion as a preprocessing step. While removing image noise, this technique preserve the significant parts of the image, typically edges, lines or other details that are important for the interpretation of the image. The segmentation task is done by using thresholding with automatic threshold values selection and finally the false liver region is eliminated using 3D connected component. The result shows that by employing the 3D anisotropic filtering, better liver segmentation results could be achieved eventhough simple segmentation technique is used.

Keywords: 3D Anisotropic Diffusion, non-linear filtering, CT Liver.

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Authors: Anderson Rocha, Pedro Miguel de Figueiredo Dinis Oliveira Gaspar

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Machine vision has been widely used in recent years in agriculture, as a tool to promote the automation of processes and increase the levels of productivity. The aim of this work is the development of a path recognition algorithm based on image processing to guide a terrestrial robot in-between tree rows. The proposed algorithm was developed using the software MATLAB, and it uses several image processing operations, such as threshold detection, morphological erosion, histogram equalization and the Hough transform, to find edge lines along tree rows on an image and to create a path to be followed by a mobile robot. To develop the algorithm, a set of images of different types of orchards was used, which made possible the construction of a method capable of identifying paths between trees of different heights and aspects. The algorithm was evaluated using several images with different characteristics of quality and the results showed that the proposed method can successfully detect a path in different types of environments.

Keywords: Agricultural mobile robot, image processing, path recognition, Hough transform.

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Authors: Mahinda P. Pathegama, Özdemir Göl

Abstract:

Extraction of edge-end-pixels is an important step for the edge linking process to achieve edge-based image segmentation. This paper presents an algorithm to extract edge-end pixels together with their directional sensitivities as an augmentation to the currently available mathematical models. The algorithm is implemented in the Java environment because of its inherent compatibility with web interfaces since its main use is envisaged to be for remote image analysis on a virtual instrumentation platform.

Keywords: edge-end pixels, image processing, imagesegmentation, pixel extraction

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Authors: Abhishek Bansal, G. N. Pillai

Abstract:

This paper presents a new method to detect high impedance faults in radial distribution systems. Magnitudes of third and fifth harmonic components of voltages and currents are used as a feature vector for fault discrimination. The proposed methodology uses a learning vector quantization (LVQ) neural network as a classifier for identifying high impedance arc-type faults. The network learns from the data obtained from simulation of a simple radial system under different fault and system conditions. Compared to a feed-forward neural network, a properly tuned LVQ network gives quicker response.

Keywords: Fault identification, distribution networks, high impedance arc-faults, feature vector, LVQ networks.

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: Deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator.

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Authors: P. S. Gomathi, B. Kalaavathi

Abstract:

The process in which the complementary information from multiple images is integrated to provide composite image that contains more information than the original input images is called image fusion. Medical image fusion provides useful information from multimodality medical images that provides additional information to the doctor for diagnosis of diseases in a better way. This paper represents the wavelet based medical image fusion algorithm on different multimodality medical images. In order to fuse the medical images, images are decomposed using Redundant Wavelet Transform (RWT). The high frequency coefficients are convolved with morphological operator followed by the maximum-selection (MS) rule. The low frequency coefficients are processed by MS rule. The reconstructed image is obtained by inverse RWT. The quantitative measures which includes Mean, Standard Deviation, Average Gradient, Spatial frequency, Edge based Similarity Measures are considered for evaluating the fused images. The performance of this proposed method is compared with Pixel averaging, PCA, and DWT fusion methods. When compared with conventional methods, the proposed framework provides better performance for analysis of multimodality medical images.

Keywords: Discrete Wavelet Transform (DWT), Image Fusion, Morphological Processing, Redundant Wavelet Transform (RWT).

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Authors: Abdelrahman Taha, Niloofar Malekghaini, Hamed Ebrahimian, Ramin Motamed

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This paper compares the substructure and direct approaches for soil-structure interaction (SSI) analysis in the time domain. In the substructure approach, the soil domain is replaced by a set of springs and dashpots, also referred to as the impedance function, derived through the study of the behavior of a massless rigid foundation. The impedance function is inherently frequency dependent, i.e., it varies as a function of the frequency content of the structural response. To use the frequency-dependent impedance function for time-domain SSI analysis, the impedance function is approximated at the fundamental frequency of the coupled soil-structure system. To explore the potential limitations of the substructure modeling process, a two-dimensional (2D) reinforced concrete frame structure is modeled and analyzed using the direct and substructure approaches. The results show discrepancy between the simulated responses of the direct and substructure models. It is concluded that the main source of discrepancy is likely attributed to the way the impedance functions are calculated, i.e., assuming a massless rigid foundation without considering the presence of the superstructure. Hence, a refined impedance function, considering the presence of the superstructure, shall alternatively be developed. This refined impedance function is expected to improve the simulation accuracy of the substructure approach.

Keywords: Direct approach, impedance function, massless rigid foundation, soil-structure interaction, substructure approach.

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Authors: Yong-Gyu Lee, Gilwon Yoon

Abstract:

Image processing for capsule endoscopy requires large memory and it takes hours for diagnosis since operation time is normally more than 8 hours. A real-time analysis algorithm of capsule images can be clinically very useful. It can differentiate abnormal tissue from health structure and provide with correlation information among the images. Bleeding is our interest in this regard and we propose a method of detecting frames with potential bleeding in real-time. Our detection algorithm is based on statistical analysis and the shapes of bleeding spots. We tested our algorithm with 30 cases of capsule endoscopy in the digestive track. Results were excellent where a sensitivity of 99% and a specificity of 97% were achieved in detecting the image frames with bleeding spots.

Keywords: bleeding, capsule endoscopy, image processing, real time analysis

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Authors: S. Shefali, S. M. Deshpande, S. G. Tamhankar

Abstract:

Now a days, a significant part of commercial and governmental organisations like museums, cultural organizations, libraries, commercial enterprises, etc. invest intensively in new technologies for image digitization, digital libraries, image archiving and retrieval. Hence image authorization, authentication and security has become prime need. In this paper, we present a semi-fragile watermarking scheme for color images. The method converts the host image into YIQ color space followed by application of orthogonal dual domains of DCT and DWT transforms. The DCT helps to separate relevant from irrelevant image content to generate silent image features. DWT has excellent spatial localisation to help aid in spatial tamper characterisation. Thus image adaptive watermark is generated based of image features which allows the sharp detection of microscopic changes to locate modifications in the image. Further, the scheme utilises the multipurpose watermark consisting of soft authenticator watermark and chrominance watermark. Which has been proved fragile to some predefined processing like intentinal fabrication of the image or forgery and robust to other incidental attacks caused in the communication channel.

Keywords: Cryptography, Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Watermarking.

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Authors: H. B. Kekre, Sudeep D. Thepade

Abstract:

The automatic construction of large, high-resolution image vistas (mosaics) is an active area of research in the fields of photogrammetry [1,2], computer vision [1,4], medical image processing [4], computer graphics [3] and biometrics [8]. Image stitching is one of the possible options to get image mosaics. Vista Creation in image processing is used to construct an image with a large field of view than that could be obtained with a single photograph. It refers to transforming and stitching multiple images into a new aggregate image without any visible seam or distortion in the overlapping areas. Vista creation process aligns two partial images over each other and blends them together. Image mosaics allow one to compensate for differences in viewing geometry. Thus they can be used to simplify tasks by simulating the condition in which the scene is viewed from a fixed position with single camera. While obtaining partial images the geometric anomalies like rotation, scaling are bound to happen. To nullify effect of rotation of partial images on process of vista creation, we are proposing rotation invariant vista creation algorithm in this paper. Rotation of partial image parts in the proposed method of vista creation may introduce some missing region in the vista. To correct this error, that is to fill the missing region further we have used image inpainting method on the created vista. This missing view regeneration method also overcomes the problem of missing view [31] in vista due to cropping, irregular boundaries of partial image parts and errors in digitization [35]. The method of missing view regeneration generates the missing view of vista using the information present in vista itself.

Keywords: Vista, Overlap Estimation, Rotation Invariance, Missing View Regeneration.

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