Bionic Mosaic Method of Panoramic Image Based on Compound Eye of Fly

To satisfy the requirements of real-time and high quality mosaics, a bionic compound eye visual system was designed by simulating the visual mechanism of a fly compound eye. Several CCD cameras were used in this system to imitate the small eyes of a compound eye. Based on the optical analysis of this system, a direct panoramic image mosaic algorithm was proposed. Several sub-images were collected by the bionic compound eye visual system, and then the system obtained the overlapping proportions of these sub-images and cut the overlap sections of the neighboring images. Thus, a panoramic image with a large field of view was directly mosaicked, which expanded the field and guaranteed the high resolution. The experimental results show that the time consumed by the direct mosaic algorithm is only 2.2% of that by the traditional image mosaic algorithm while guaranteeing mosaic quality. Furthermore, the proposed method effectively solved the problem of misalignment of the mosaic image and eliminated mosaic cracks as a result of the illumination factor and other factors. This method has better real-time properties compared to other methods.

A 360-Degree Panoramic Image Inpainting Network Using a Cube Map

Inpainting has been continuously studied in the field of computer vision.As artificial intelligence technology developed,deep learning technology was introduced in inpainting research,helping to improve performance.Currently,the input target of an inpainting algorithm using deep learning has been studied from a single image to a video.However,deep learning-based inpainting technology for panoramic images has not been actively studied.We propose a 360-degree panoramic image inpainting method using generative adversarial networks(GANs).The proposed network inputs a 360-degree equirectangular format panoramic image converts it into a cube map format,which has relatively little distortion and uses it as a training network.Since the cube map format is used,the correlation of the six sides of the cube map should be considered.Therefore,all faces of the cube map are used as input for the whole discriminative network,and each face of the cube map is used as input for the slice discriminative network to determine the authenticity of the generated image.The proposed network performed qualitatively better than existing single-image inpainting algorithms and baseline algorithms.

Real-time parameters monitoring system for underground equipment based on panoramic images

Complex terrain and working equipment in coal mine underground need a way to ensure coal mine safety. In this paper, the way to monitor the real-time status of underground equipment was put forward, and it was proved to be effective as commanding and dispatching system. Monitoring system for underground equipment based on panoramic images was effectively combined with real-time sensor data and static panoramic images of underground surrounding, which not only realizes real-time status monitoring for underground equipment, but also gets a direct scene for underground surrounding. B/S mode was applied in the monitoring system and this is convenient for users to monitor the equipment. Meantime, it can reduce the waste of the data resource.

Electronic stabilization of catadioptric panoramic image

An effective algorithm of electronic image stabilization （EIS） of catadioptric panoramic imaging system for track robots is presented. The key techniques of this algorithm are as follows：① A model of electronic image stabilization is built by analyzing the imaging theory and the principle of EIS, and the image shift function of unwrapped panoramic image is deduced;② The relationship equation between motion estimation parameters of annular panoramic image and motion estimation parameters of unwrapped panoramic image is developed according to the constrained aspect ratio of real objects, motion parameters of annular panoramic image are firstly estimated, and then motion parameters among the image shift function are carried out according to the relationship equation;③ An excessive stabilization threshold is presented to prevent the phenomena of excessive stabilization, and the Kalman filtering is adopted to smooth the image sequences. Numerical experimental results show that this algorithm can effectively smooth out the unwanted motion and follow the intentional camera movement under certain resolutions.

Intelligent extraction of road cracks based on vehicle laser point cloud and panoramic sequence images

In light of the limited efficacy of conventional methods for identifying pavement cracks and the absence of comprehensive depth and location data in two-dimensional photographs,this study presents an intelligent strategy for extracting road cracks.This methodology involves the integration of laser point cloud data obtained from a vehicle-mounted system and a panoramic sequence of images.The study employs a vehicle-mounted LiDAR measurement system to acquire laser point cloud and panoramic sequence image data simultaneously.A convolutional neural network is utilized to extract cracks from the panoramic sequence image.The extracted sequence image is then aligned with the laser point cloud,enabling the assignment of RGB information to the vehicle-mounted three dimensional(3D)point cloud and location information to the two dimensional(2D)panoramic image.Additionally,a threshold value is set based on the crack elevation change to extract the aligned roadway point cloud.The three-dimensional data pertaining to the cracks can be acquired.The experimental findings demonstrate that the use of convolutional neural networks has yielded noteworthy outcomes in the extraction of road cracks.The utilization of point cloud and image alignment techniques enables the extraction of precise location data pertaining to road cracks.This approach exhibits superior accuracy when compared to conventional methods.Moreover,it facilitates rapid and accurate identification and localization of road cracks,thereby playing a crucial role in ensuring road maintenance and traffic safety.Consequently,this technique finds extensive application in the domains of intelligent transportation and urbanization development.The technology exhibits significant promise for use in the domains of intelligent transportation and city development.

Research and Implementation of Algorithm for Image Enhancement and Unwrapped Distortion Correction for SLVF Panoramic Night Vision Image

Abstract： Based on digital signal processor（DSP） and field programmable gate array（FPGA） techniques, the architecture of super large view field（SLVF） panoramic night vision image processing hardware platform was established. The panoramic unwrapping and correcting algorithm, up to a full 360°, based on coordinate rotation digital computer （CORDIC） and night vision image enhancement algorithm, based on histogram equalization theory and edge detection theory, was presented in this paper, with the purpose of processing night vision dynamic panoramic annular image. The annular image can be unwrapped and corrected to conventional rectangular panorama by the panoramic image processing algorithm, which uses the pipelined CORDIC configuration to realize a trigonometric function generator with high speed and high precision. Histogram equalization algorithm can perfectly enhance the contrast of the night vision image. Edge detection algorithm can be propitious to find and detect small dim dynamic targets in night vision circumstances. After abundant experiment, the al- gorithm for panoramic image processing and night vision image enhancement is successfully implemented in FPGA and DSP. The panoramic night vision image system is a compact device, with no external rotating parts. And the system can reliably and dynamically detect 360＊ SLVF panoramic night vision image.

CIRCUMFERENTIAL EQUISPACED CURVES'S IMAGE DETECTION TECHNIQUE AND ITS APPLAICATION ON RIFLING ANGLE MEASUREMENT

Aiming at the parameter detection of the circumferential equispaced curves,and on the background of the rifling parameter detection, a panoramic image based detectiontechnique is proposed, which employs the panoramic image photographed by a tamper reflector and aCCD camera to detect the parameter of the circumferential equispaced curves. The effect of thesystem's off-center error, deflection error and pixel error on the parameter detection is analyzed,which shows that this technique make a good use of the property of the circumferential equispaced,and has a high power of anti off-center error and anti deflection error, resulting a high precisionat the parameter measurement on circumferential equispaced curves.

Panoramic Imaging System Inspired by Insect Compound Eyes

Inspired by the unique structure of insect compound eyes,a multi-channel image acquisition system is designed to photograph a cylindrical panorama of its surroundings with one shot. The hardware structure consists of an embedded ARM system and one array of 16 micro-image sensors. The system achieves the synchronization of captured photos in 10 ms,as well as 10 f /s video capture. The software architecture includes the TCP /IP protocol,video capture procedures in"Poll/Read"or"video streaming"modes,thread pool monitoring in multi-threading mutex,synchronization control with the"event""mutex signal"and"critical region"functions,and a synthetic image algorithm characterized by its portability,modularity,and remote transmission. The panoramic imaging system is expected to be a vision sensor for mobile robotics.

Fully Convolutional Networks for Street Furniture Identification in Panorama Images

Panoramic images are widely used in many scenes,especially in virtual reality and street view capture.However,they are new for street furniture identification which is usually based on mobile laser scanning point cloud data or conventional 2D images.This study proposes to perform semantic segmentation on panoramic images and transformed images to separate light poles and traffic signs from background implemented by pre-trained Fully Convolutional Networks(FCN).FCN is the most important model for deep learning applied on semantic segmentation for its end to end training process and pixel-wise prediction.In this study,we use FCN-8s model that pre-trained on cityscape dataset and finetune it by our own data.Then replace cross entropy loss function with focal loss function in the FCN model and train it again to produce the predictions.The results show that in all results from pre-trained model,fine-tuning,and FCN model with focal loss,the light poles and traffic signs are detected well and the transformed images have better performance than panoramic images in the prediction according to the Recall and IoU evaluation.

Perceptual quality assessment of panoramic stitched contents for immersive applications:a prospective survey

The recent advancements in the field of Virtual Reality(VR)and Augmented Reality(AR)have a substantial impact on modern day technology by digitizing each and everything related to human life and open the doors to the next generation Software Technology(Soft Tech).VR and AR technology provide astonishing immersive contents with the help of high quality stitched panoramic contents and 360°imagery that widely used in the education,gaming,entertainment,and production sector.The immersive quality of VR and AR contents are greatly dependent on the perceptual quality of panoramic or 360°images,in fact a minor visual distortion can significantly degrade the overall quality.Thus,to ensure the quality of constructed panoramic contents for VR and AR applications,numerous Stitched Image Quality Assessment(SIQA)methods have been proposed to assess the quality of panoramic contents before using in VR and AR.In this survey,we provide a detailed overview of the SIQA literature and exclusively focus on objective SIQA methods presented till date.For better understanding,the objective SIQA methods are classified into two classes namely Full-Reference SIQA and No-Reference SIQA approaches.Each class is further categorized into traditional and deep learning-based methods and examined their performance for SIQA task.Further,we shortlist the publicly available benchmark SIQA datasets and evaluation metrices used for quality assessment of panoramic contents.In last,we highlight the current challenges in this area based on the existing SIQA methods and suggest future research directions that need to be target for further improvement in SIQA domain.

Integration and application of panorama field geological images and Google maps

Panorama field geological image is an important form of displaying field geology information with high resolution.Taking an example for Xingcheng,the authors studied the use of panorama field geological images based on the Flex for rich client display technology,application of Google maps API for Flash,and discussed construction method for field geological panoramic information system which created the rich client Internet application program.The results indicate that using Google maps API to mark position and route of panoramic image collection point can be fully integrated field geological information and map information.It can provide visual field geological information for users.This program is characterized by quick execution speed,strong interaction and rich function,which promotes the users'experience effectively.

Terrain reconstruction from Chang'e-3 PCAM images

The existing terrain models that describe the local lunar surface have limited resolution and accuracy, which can hardly meet the needs of rover navigation,positioning and geological analysis. China launched the lunar probe Chang＇e-3 in December, 2013. Chang＇e-3 encompassed a lander and a lunar rover called ＂Yutu＂（Jade Rabbit）. A set of panoramic cameras were installed on the rover mast. After acquiring panoramic images of four sites that were explored, the terrain models of the local lunar surface with resolution of 0.02 m were reconstructed. Compared with other data sources, the models derived from Chang＇e-3 data were clear and accurate enough that they could be used to plan the route of Yutu.

Method for evaluation of geological strength index of carbonate cliff rocks:Coupled hyperspectral-digital borehole image technique

The deterioration of unstable rock mass raised interest in evaluating rock mass quality.However,the traditional evaluation method for the geological strength index(GSI)primarily emphasizes the rock structure and characteristics of discontinuities.It ignores the influence of mineral composition and shows a deficiency in assessing the integrity coefficient.In this context,hyperspectral imaging and digital panoramic borehole camera technologies are applied to analyze the mineral content and integrity of rock mass.Based on the carbonate mineral content and fissure area ratio,the strength reduction factor and integrity coefficient are calculated to improve the GSI evaluation method.According to the results of mineral classification and fissure identification,the strength reduction factor and integrity coefficient increase with the depth of rock mass.The rock mass GSI calculated by the improved method is mainly concentrated between 40 and 60,which is close to the calculation results of the traditional method.The GSI error rates obtained by the two methods are mostly less than 10%,indicating the rationality of the hyperspectral-digital borehole image coupled evaluation method.Moreover,the sensitivity of the fissure area ratio(Sr)to GSI is greater than that of the strength reduction factor(a),which means the proposed GSI is suitable for rocks with significant fissure development.The improved method reduces the influence of subjective factors and provides a reliable index for the deterioration evaluation of rock mass.

An Image-Based Virtual Reality Prototype System

The most important goal of virtual reality is to create a virtual world by computers where users are allowed to view the environment and control the virtual objects interactively. naditionally virtual reality systems use 3D computer graphics to model and render a virtual environment in real time. However, this approach usually requires laborious modeling and expensive special-purpose rendering hardware. Image-based rendering is a new approach in composing a virtual environment in which a set of panoramic images is used to compose the virtual environment and walking in the space is accomplished by 'hopping' to different panoramic points. This paper introduces an experimeatal image-based VR system. The techniques utilized in the system, in particular the authoring and interactive control tools of the system, are described in detail.