Long Range Automated Persistent Surveillance

This dissertation addresses long range automated persistent surveillance with focus on three topics: sensor planning, size preserving tracking, and high magnification imaging. field of view should be reserved so that camera handoff can be executed successfully before the object of interest becomes unidentifiable or untraceable. We design a sensor planning algorithm that not only maximizes coverage but also ensures uniform and sufficient overlapped camera’s field of view for an optimal handoff success rate. This algorithm works for environments with multiple dynamic targets using different types of cameras. Significantly improved handoff success rates are illustrated via experiments using floor plans of various scales. Size preserving tracking automatically adjusts the camera’s zoom for a consistent view of the object of interest. Target scale estimation is carried out based on the paraperspective projection model which compensates for the center offset and considers system latency and tracking errors. A computationally efficient foreground segmentation strategy, 3D affine shapes, is proposed. The 3D affine shapes feature direct and real-time implementation and improved flexibility in accommodating the target’s 3D motion, including off-plane rotations. The effectiveness of the scale estimation and foreground segmentation algorithms is validated via both offline and real-time tracking of pedestrians at various resolution levels. Face image quality assessment and enhancement compensate for the performance degradations in face recognition rates caused by high system magnifications and long observation distances. A class of adaptive sharpness measures is proposed to evaluate and predict this degradation. A wavelet based enhancement algorithm with automated frame selection is developed and proves efficient by a considerably elevated face recognition rate for severely blurred long range face images

Super-Resolution of Unmanned Airborne Vehicle Images with Maximum Fidelity Stochastic Restoration

Super-resolution (SR) refers to reconstructing a single high resolution (HR) image from a set of subsampled, blurred and noisy low resolution (LR) images. One may, then, envision a scenario where a set of LR images is acquired with sensors on a moving platform like unmanned airborne vehicles (UAV). Due to the wind, the UAV may encounter altitude change or rotational effects which can distort the acquired as well as the processed images. Also, the visual quality of the SR image is affected by image acquisition degradations, the available number of the LR images and their relative positions. This dissertation seeks to develop a novel fast stochastic algorithm to reconstruct a single SR image from UAV-captured images in two steps. First, the UAV LR images are aligned using a new hybrid registration algorithm within subpixel accuracy. In the second step, the proposed approach develops a new fast stochastic minimum square constrained Wiener restoration filter for SR reconstruction and restoration using a fully detailed continuous-discrete-continuous (CDC) model. A new parameter that accounts for LR images registration and fusion errors is added to the SR CDC model in addition to a multi-response restoration and reconstruction. Finally, to assess the visual quality of the resultant images, two figures of merit are introduced: information rate and maximum realizable fidelity. Experimental results show that quantitative assessment using the proposed figures coincided with the visual qualitative assessment. We evaluated our filter against other SR techniques and its results were found to be competitive in terms of speed and visual quality

Development of Some Spatial-domain Preprocessing and Post-processing Algorithms for Better 2-D Up-scaling

Image super-resolution is an area of great interest in recent years and is extensively used in applications like video streaming, multimedia, internet technologies, consumer electronics, display and printing industries. Image super-resolution is a process of increasing the resolution of a given image without losing its integrity. Its most common application is to provide better visual effect after resizing a digital image for display or printing. One of the methods of improving the image resolution is through the employment of a 2-D interpolation. An up-scaled image should retain all the image details with very less degree of blurring meant for better visual quality. In literature, many efficient 2-D interpolation schemes are found that well preserve the image details in the up-scaled images; particularly at the regions with edges and fine details. Nevertheless, these existing interpolation schemes too give blurring effect in the up-scaled images due to the high frequency (HF) degradation during the up-sampling process. Hence, there is a scope to further improve their performance through the incorporation of various spatial domain pre-processing, post-processing and composite algorithms. Therefore, it is felt that there is sufficient scope to develop various efficient but simple pre-processing, post-processing and composite schemes to effectively restore the HF contents in the up-scaled images for various online and off-line applications. An efficient and widely used Lanczos-3 interpolation is taken for further performance improvement through the incorporation of various proposed algorithms. The various pre-processing algorithms developed in this thesis are summarized here. The term pre-processing refers to processing the low-resolution input image prior to image up-scaling. The various pre-processing algorithms proposed in this thesis are: Laplacian of Laplacian based global pre-processing (LLGP) scheme; Hybrid global pre-processing (HGP); Iterative Laplacian of Laplacian based global pre-processing (ILLGP); Unsharp masking based pre-processing (UMP); Iterative unsharp masking (IUM); Error based up-sampling(EU) scheme. The proposed algorithms: LLGP, HGP and ILLGP are three spatial domain preprocessing algorithms which are based on 4th, 6th and 8th order derivatives to alleviate nonuniform blurring in up-scaled images. These algorithms are used to obtain the high frequency (HF) extracts from an image by employing higher order derivatives and perform precise sharpening on a low resolution image to alleviate the blurring in its 2-D up-sampled counterpart. In case of unsharp masking based pre-processing (UMP) scheme, the blurred version of a low resolution image is used for HF extraction from the original version through image subtraction. The weighted version of the HF extracts are superimposed with the original image to produce a sharpened image prior to image up-scaling to counter blurring effectively. IUM makes use of many iterations to generate an unsharp mask which contains very high frequency (VHF) components. The VHF extract is the result of signal decomposition in terms of sub-bands using the concept of analysis filter bank. Since the degradation of VHF components is maximum, restoration of such components would produce much better restoration performance. EU is another pre-processing scheme in which the HF degradation due to image upscaling is extracted and is called prediction error. The prediction error contains the lost high frequency components. When this error is superimposed on the low resolution image prior to image up-sampling, blurring is considerably reduced in the up-scaled images. Various post-processing algorithms developed in this thesis are summarized in following. The term post-processing refers to processing the high resolution up-scaled image. The various post-processing algorithms proposed in this thesis are: Local adaptive Laplacian (LAL); Fuzzy weighted Laplacian (FWL); Legendre functional link artificial neural network(LFLANN). LAL is a non-fuzzy, local based scheme. The local regions of an up-scaled image with high variance are sharpened more than the region with moderate or low variance by employing a local adaptive Laplacian kernel. The weights of the LAL kernel are varied as per the normalized local variance so as to provide more degree of HF enhancement to high variance regions than the low variance counterpart to effectively counter the non-uniform blurring. Furthermore, FWL post-processing scheme with a higher degree of non-linearity is proposed to further improve the performance of LAL. FWL, being a fuzzy based mapping scheme, is highly nonlinear to resolve the blurring problem more effectively than LAL which employs a linear mapping. Another LFLANN based post-processing scheme is proposed here to minimize the cost function so as to reduce the blurring in a 2-D up-scaled image. Legendre polynomials are used for functional expansion of the input pattern-vector and provide high degree of nonlinearity. Therefore, the requirement of multiple layers can be replaced by single layer LFLANN architecture so as to reduce the cost function effectively for better restoration performance. With single layer architecture, it has reduced the computational complexity and hence is suitable for various real-time applications. There is a scope of further improvement of the stand-alone pre-processing and postprocessing schemes by combining them through composite schemes. Here, two spatial domain composite schemes, CS-I and CS-II are proposed to tackle non-uniform blurring in an up-scaled image. CS-I is developed by combining global iterative Laplacian (GIL) preprocessing scheme with LAL post-processing scheme. Another highly nonlinear composite scheme, CS-II is proposed which combines ILLGP scheme with a fuzzy weighted Laplacian post-processing scheme for more improved performance than the stand-alone schemes. Finally, it is observed that the proposed algorithms: ILLGP, IUM, FWL, LFLANN and CS-II are better algorithms in their respective categories for effectively reducing blurring in the up-scaled images

Correction of spherical single lens aberration using digital image processing for cellular phone camera

制度:新 ; 報告番号:甲3276号 ; 学位の種類:博士(工学) ; 授与年月日:2011/2/21 ; 早大学位記番号:新558

Experimental studies on shock wave interactions with flexible surfaces and development of flow diagnostic tools

Nowadays, light-weight composite materials have increasingly used for high-speed flight vehicles to improve their performance and efficiency. At supersonic speed, sonic fatigue, panel flutter, severe instabilities, and even catastrophic structural failure would occur due to the shock wave impingement on several flexible components of a given structural system either internally or externally. Therefore, investigation on shock wave interaction with flexible surfaces is crucial for the safety and performance of high-speed flight vehicles. This work aims to investigate the mechanism of shock wave interaction with flexible surfaces with and without the presence of the boundary layer. The first part involves the shock wave generated by supersonic starting jets interaction with flexible surfaces and the other one focuses on shock wave and boundary layer interaction (SBLI) over flexible surfaces. A novel miniature and cost-effective shock tube driven by detonation transmission tubing was designed and manufactured to simulate the supersonic starting jet and investigate the interaction of a supersonic starting jet with flexible surfaces. To investigate the characterization of this novel type shock tube, the pressure-time measurement in the driven section and the time-resolved shadowgraph were performed. The result shows that the flow structure from the open end of the shock tube driven by detonation transmission tubing agrees with that of conventional compressed-gas driven shock tubes. Moreover, this novel type of shock tube has good repeatability of less than 3% with a Mach number range of 1.29-1.58 when the weight of the NONEL explosive mixture varies from 3.6mg to 12.6mg. An unsteady background oriented schlieren (BOS) measurement system and a sprayable Polymer-Ceramic unsteady pressure sensitive paint (PC-PSP) system were developed. The preliminary BOS result in a supersonic wind tunnel shows that the sensitivity of the BOS system is good enough to visualize weak density variations caused by expansion waves, boundary layer, and weak oblique shocks. Additionally, compared with the commercial PC-PSP from Innovative Scientific Solutions Incorporated (ISSI), the in-house developed unsteady PSP system has higher pressure sensitivity, lower temperature sensitivity, and photo-degradation rate. To identify the shock movement, distortion and unsteadiness during the processes of the supersonic starting jet impingement and shock wave boundary layer interaction (SBLI) over flexible surfaces, an image processing scheme involving background subtraction in the frequency domain, filtering, resampling, edge detection, adaptive threshold, contour detection, feature extraction, and fitting was proposed and applied to process shadowgraph and schlieren sequences automatically. A large shadowgraph data set characterized by low signal to noise ratio (SNR) and small spatial resolution (312×260-pixel), was used to validate the proposed scheme. The result proves that the aforementioned image processing scheme can detect, track, localize, and fit shock waves in a subpixel accuracy. The mechanism of the interaction between the initial shock wave from a supersonic starting jet and flexible surfaces was investigated based on a square shock tube driven by detonation transmitting tube. Compared with that of the solid plate case, flexible surfaces can delay the shock reflection process because of the flexible panel deformation generated by the pressure difference between the top and the bottom. The delay time is around 8µs in the case of 0.1mm thick flexible surface, whereas it declines to around 4µs in the case of 0.3mm thick flexible surface because of the lower flexibility and deformation magnitude. However, interestingly, the propagation velocity of the reflected shock wave is basically the same for the solid plate and flexible panels, which means the flexible surface doesn’t reduce the strength of the reflection wave, although it delays its propagation. Also, there is not an apparent difference in the velocity of the reflected shock wave in the case of different incident shock Mach numbers when Ms varying from 1.22 to 1.54. These experimental results from this study are useful for validating numerical codes that are used for understanding fluid-structure interaction processes

Image Registration Workshop Proceedings

Automatic image registration has often been considered as a preliminary step for higher-level processing, such as object recognition or data fusion. But with the unprecedented amounts of data which are being and will continue to be generated by newly developed sensors, the very topic of automatic image registration has become and important research topic. This workshop presents a collection of very high quality work which has been grouped in four main areas: (1) theoretical aspects of image registration; (2) applications to satellite imagery; (3) applications to medical imagery; and (4) image registration for computer vision research

Embodied gestures

This is a book about musical gestures: multiple ways to design instruments, compose musical performances, analyze sound objects and represent sonic ideas through the central notion of ‘gesture’. The writers share knowledge on major research projects, musical compositions and methodological tools developed among different disciplines, such as sound art, embodied music cognition, human-computer interaction, performative studies and artificial intelligence. They visualize how similar and compatible are the notions of embodied music cognition and the artistic discourses proposed by musicians working with ‘gesture’ as their compositional material. The authors and editors hope to contribute to the ongoing discussion around creative technologies and music, expressive musical interface design, the debate around the use of AI technology in music practice, as well as presenting a new way of thinking about musical instruments, composing and performing with them

Plant Seed Identification

Plant seed identification is routinely performed for seed certification in seed trade, phytosanitary certification for the import and export of agricultural commodities, and regulatory monitoring, surveillance, and enforcement. Current identification is performed manually by seed analysts with limited aiding tools. Extensive expertise and time is required, especially for small, morphologically similar seeds. Computers are, however, especially good at recognizing subtle differences that humans find difficult to perceive. In this thesis, a 2D, image-based computer-assisted approach is proposed. The size of plant seeds is extremely small compared with daily objects. The microscopic images of plant seeds are usually degraded by defocus blur due to the high magnification of the imaging equipment. It is necessary and beneficial to differentiate the in-focus and blurred regions given that only sharp regions carry distinctive information usually for identification. If the object of interest, the plant seed in this case, is in- focus under a single image frame, the amount of defocus blur can be employed as a cue to separate the object and the cluttered background. If the defocus blur is too strong to obscure the object itself, sharp regions of multiple image frames acquired at different focal distance can be merged together to make an all-in-focus image. This thesis describes a novel non-reference sharpness metric which exploits the distribution difference of uniform LBP patterns in blurred and non-blurred image regions. It runs in realtime on a single core cpu and responses much better on low contrast sharp regions than the competitor metrics. Its benefits are shown both in defocus segmentation and focal stacking. With the obtained all-in-focus seed image, a scale-wise pooling method is proposed to construct its feature representation. Since the imaging settings in lab testing are well constrained, the seed objects in the acquired image can be assumed to have measureable scale and controllable scale variance. The proposed method utilizes real pixel scale information and allows for accurate comparison of seeds across scales. By cross-validation on our high quality seed image dataset, better identification rate (95%) was achieved compared with pre- trained convolutional-neural-network-based models (93.6%). It offers an alternative method for image based identification with all-in-focus object images of limited scale variance. The very first digital seed identification tool of its kind was built and deployed for test in the seed laboratory of Canadian food inspection agency (CFIA). The proposed focal stacking algorithm was employed to create all-in-focus images, whereas scale-wise pooling feature representation was used as the image signature. Throughput, workload, and identification rate were evaluated and seed analysts reported significantly lower mental demand (p = 0.00245) when using the provided tool compared with manual identification. Although the identification rate in practical test is only around 50%, I have demonstrated common mistakes that have been made in the imaging process and possible ways to deploy the tool to improve the recognition rate

Nostalgic Frontiers: Violence Across the Midwest in Popular Film

In Nostalgic Frontiers: Violence Across the Midwest in Popular Film, I analyze the temporality and politics of nostalgia while providing a critical history of Midwestern representations in popular culture from the turn of the twentieth century through the first decade of the new millennium. A general line of inquiry informs this project: how do narratives set in the Midwest imagine, reify, and reproduce Midwestern identity, and what are the repercussions of such regional imagery circulating in American culture? Throughout this project, I identify shifting cultural perceptions of the Midwest at particular historical moments. In relation to these regional considerations, I analyze two modes of nostalgia: as a spatial element that is mapped onto the Midwest\u27s landscape and as a cultural force that regulates Midwesterners with violence. I developed the concept of nostalgic violence in order to theorize violent attempts to reshape the present in relation to idealized images of the past in Midwestern narratives. Overall, with Nostalgic Frontiers, I work to more fully integrate nostalgia and regional study into the diverse field of media studies by assessing how ideological and historical factors are filtered through cinema, thus shaping our understanding of the Midwest