Generating video animation from single still image in social media based on intelligent computing

Bringing a single still image into reality is a challenging topic in computer animation because the driven and structural information in single still image is inadequate. In this paper, we present an image animating method for enhancing single still image in social media with virtual realistic and animated motions without prior information. We imitate the interaction between the active objects in an image and their neighboring passive objects. The existing actions in the image and the virtual specified force are employed to animate the active objects. Observing that the change between two subsequent motions of the active objects derives a motion tendency, we can calculate a virtual driving force based on the motion tendency. By virtue of the virtual driving force, the stochastic motion texture is used to animate the passive objects. Finally, the convolutional neural network is employed to optimize the virtual motion animations. In this way, the proposed method produces visually natural results while guaranteeing motion harmony between active objects and passive objects. To demonstrate the applicability and rationality of virtual animation driving force, our method generates several animations from still images in Social Media.     

Jointly registering and fusing images from multiple sensors

In this paper, a novel approach is proposed for jointly registering and fusing a multisensor ensemble of images. Based on the idea that both groupwise registration and fusion can be treated as estimation problems, the proposed approach simultaneously models the mapping from the fused image to the source images and the joint intensity of all images with motion parameters at first, and then combines these models into a maximum likelihood function. The relevant parameters are determined through employing an expectation maximization algorithm. To evaluate the performance of the proposed approach, some representative image registration and fusion approaches are compared on different multimodal image datasets. The criterion, which is defined as the average pixel displacement from its true registered position, is used to compare the performances of registration approaches. As for evaluating the fusion performance, three fusion quality measures which are metric Q^ab/f, mutual information and average gradient are employed. The experimental results show that the proposed approach has improved performance compared to conventional approaches.     

Numerical study on premixed hydrogen/air combustion characteristics and heat transfer enhancement of micro-combustor embedded with pin fins

Aimed at improving the energy output performance of the Microthermal Photovoltaic (MTPV) system, it is necessary to optimize the structure of the micro combustor. In this paper, micro combustor with in-line pin fins arrays (MCIPF) and micro combustor with both end-line pin fins arrays (MCEPF) were presented to realize the efficient combustion and heat transfer enhancement, and the influence of inlet velocity, equivalent ratio, and materials on thermal performance was investigated. The results showed that pin fins embedding is beneficial to improving combustion, and the combustion efficiency of MCIPF and MCEPF reaches 98.5% and 98.7%, which is significantly higher than that of the conventional cylindrical combustor (MCC). However, with the increase of inlet velocity from 8 m/s to 14 m/s, MCIPF exhibits the highest external wall temperature with a range of (1302–1386 K), while MCEPF maintains the best temperature uniformity. As the inlet velocity increases to 10 m/s, the external wall temperature and temperature uniformity reach the optimum. Besides, under the conditions of different equivalence ratios, both external wall temperature and heat flux increases first and then decreases, meanwhile the temperature uniformity of MCEPF is significantly improved compared with that of MCIPF, they all exhibit the highest external wall temperature with an equivalence ratio of 1.1, and the thermal performance is greatly enhanced. By comparing the heat transfer performance of combustors with different materials based on MCEPF, it is interesting to find that the application of high thermal conductivity materials can not only increase the external wall temperature, but also improve the temperature uniformity. Therefore, materials with high thermal conductivity such as Aluminum, Red Copper and Silicon Carbide should be selected for application in micro combustors and their components. The current work provides a new design method for the enhanced heat transfer of the micro combustor.     

Difference Detection Between Two Images for Image Monitoring

In manufacturing industries, images are commonly used for quality control purposes. In such applications, if the quality of the products is good, then their images should be all similar to the image of a good-quality product. Therefore, comparison of images is a fundamental task in image-based quality control. This problem, however, is complicated in the sense that (1) observed images often contain noise, and (2) the related images need to be geometrically matched up first because images of different products could be geometrically mismatched because the relative positions between a camera and different products are often not exactly the same. The first issue requires a statistical method that can remove noise, and the second issue is related to the so-called image registration problem in the image processing literature. In this article, we propose effective methods for detecting difference between two images of products, and our proposed methods can accommodate both noise and geometric mismatch mentioned above. Theoretical results and numerical examples show that they can work effectively in applications.     

Quality assessment for color correction-based stitched images via bi-directional matching

With the deepening of social information, the panoramic image has drawn a significant interest of viewers and researchers as it can provide a very wide field of view (FoV). Since panoramic images are usually obtained by capturing images with the overlapping regions and then stitching them together, image stitching plays an important role in generating panoramic images. In order to effectively evaluate the quality of stitched images, a novel quality assessment method based on bi-directional matching is proposed for stitched images. Specifically, dense correspondences between the testing and benchmark stitched images are first established by bi-directional SIFT-flow matching. Then, color-aware, geometric-aware and structure-aware features are respectively extracted and fused via support vector regression (SVR) to obtain the final quality score. Experiments on our newly constructed database and ISIQA database demonstrate that the proposed method can achieve comparable performance compared with the conventional blind quality metrics and the quality metrics specially designed for stitched images.     

A tutorial on the segmentation of metallographic images: Taxonomy,new MetalDAM dataset,deep learning-based ensemble model,experimental analysis and challenges

Image segmentation is an important issue in many industrial processes, with high potential to enhance the manufacturing process derived from raw material imaging. For example, metal phases contained in microstructures yield information on the physical properties of the steel. Existing prior literature has been devoted to develop specific computer vision techniques able to tackle a single problem involving a particular type of metallographic image. However, the field lacks a comprehensive tutorial on the different types of techniques, methodologies, their generalizations and the algorithms that can be applied in each scenario. This paper aims to fill this gap. First, the typologies of computer vision techniques to perform the segmentation of metallographic images are reviewed and categorized in a taxonomy. Second, the potential utilization of pixel similarity is discussed by introducing novel deep learning-based ensemble techniques that exploit this information. Third, a thorough comparison of the reviewed techniques is carried out in two openly available real-world datasets, one of them being a newly published dataset directly provided by ArcelorMittal, which opens up the discussion on the strengths and weaknesses of each technique and the appropriate application framework for each one. Finally, the open challenges in the topic are discussed, aiming to provide guidance in future research to cover the existing gaps.     

A novel 4D resolution imaging method for low and medium atomic number objects at the centimeter scale by coincidence detection technique of cosmic-ray muon and its secondary particles

The muon radiography imaging technique for high-atomic-number objects(Z) and large-volume objects via muon transmission imaging and muon multiple scattering imaging remains a popular topic in the field of radiation detection imaging. However, few imaging studies have been reported on low and medium Z objects at the centimeter scale. This paper presents an imaging system that consists of three layers of a position-sensitive detector and four plastic scintillation detectors. It acquires data by co...     

Application of fuzzy image restoration in criminal investigation

The advancement of science and technology has a positive effect on the development of law disciplines. The development of algorithms and artificial intelligence also has a certain impact on judicial practice. Image restoration is a significant technique in image processing. It aims to objectively restore the content or quality of the original image from the degraded image. Image degradation is always generated in image transmission, such as distortion, blur. In modern video surveillance system, image restoration is significant for criminal investigation. However, image restoration based on conventional filter algorithms cannot achieve satisfactory performance. Thus, we first introduce the image restoration algorithms based on different degradation model. Then, we propose some applications of fuzzy image restoration in criminal investigation. We conduct experiments on both degraded images and videos and experimental results have shown the effectiveness of fuzzy image restoration applying to the criminal investigation.     

An image pixel based variational model for histogram equalization

In this paper, we develop an image pixel based histogram equalization model for image contrast enhancement. The approach is to propose a variational model containing an energy functional to adjust the pixel values of an input image directly so that the resulting histogram can be redistributed to be uniform. This idea is different from existing histogram equalization algorithms where a histogram based on the input image is constructed, a mapping is determined to output a uniform histogram and then the pixel values of the input image are adjusted based on the mapping. In the variational model, a mean brightness term is incorporated to preserve the brightness of the input image, and a geometry constraint can also be added to keep the geometry structure of the input image. Theoretically, the existence of the minimizer of the proposed model, and the convergence of the proposed algorithm are given. Experimental results are reported to demonstrate that the performance of the proposed model are competitive with the other testing histogram equalization methods for several testing images.     

Organic Additives for the Enhancement of Laminar Flow in a Brain‐Vessels‐Like Microchannel Assembly

Organic polymers were extracted from okra, aloe vera, and hibiscus leaves and used as drag‐reducing additives (DRAs) to enhance the laminar flow in custom‐made microchannels that simulate the human brain vessels. The experiment was conducted using an open‐loop microfluidic system. The flow enhancement performance was evaluated as the function of percentage of flow increment of mucilage additives at different concentrations. Okra mucilage showed greater flow enhancement performance at higher mucilage concentration while both aloe vera and hibiscus mucilage performed better at lower additive concentration. The findings prove the potential of these organic polymers as DRAs to enhance the blood flow.