Efficient Irregular Wavefront Propagation Algorithms on Hybrid CPU-GPU Machines

In this paper, we address the problem of efficient execution of a computation pattern, referred to here as the irregular wavefront propagation pattern (IWPP), on hybrid systems with multiple CPUs and GPUs. The IWPP is common in several image processing operations. In the IWPP, data elements in the wavefront propagate waves to their neighboring elements on a grid if a propagation condition is satisfied. Elements receiving the propagated waves become part of the wavefront. This pattern results in irregular data accesses and computations. We develop and evaluate strategies for efficient computation and propagation of wavefronts using a multi-level queue structure. This queue structure improves the utilization of fast memories in a GPU and reduces synchronization overheads. We also develop a tile-based parallelization strategy to support execution on multiple CPUs and GPUs. We evaluate our approaches on a state-of-the-art GPU accelerated machine (equipped with 3 GPUs and 2 multicore CPUs) using the IWPP implementations of two widely used image processing operations: morphological reconstruction and euclidean distance transform. Our results show significant performance improvements on GPUs. The use of multiple CPUs and GPUs cooperatively attains speedups of 50x and 85x with respect to single core CPU executions for morphological reconstruction and euclidean distance transform, respectively.Comment: 37 pages, 16 figure

Characterizing neuromorphologic alterations with additive shape functionals

The complexity of a neuronal cell shape is known to be related to its function. Specifically, among other indicators, a decreased complexity in the dendritic trees of cortical pyramidal neurons has been associated with mental retardation. In this paper we develop a procedure to address the characterization of morphological changes induced in cultured neurons by over-expressing a gene involved in mental retardation. Measures associated with the multiscale connectivity, an additive image functional, are found to give a reasonable separation criterion between two categories of cells. One category consists of a control group and two transfected groups of neurons, and the other, a class of cat ganglionary cells. The reported framework also identified a trend towards lower complexity in one of the transfected groups. Such results establish the suggested measures as an effective descriptors of cell shape

Image watermarking, steganography, and morphological processing

With the fast development of computer technology, research in the fields of multimedia security, image processing, and robot vision have recently become popular. Image watermarking, steganogrphic system, morphological processing and shortest path planning are important subjects among them. In this dissertation, the fundamental techniques are reviewed first followed by the presentation of novel algorithms and theorems for these three subjects. The research on multimedia security consists of two parts, image watermarking and steganographic system. In image watermarking, several algorithms are developed to achieve different goals as shown below. In order to embed more watermarks and to minimize distortion of watermarked images, a novel watermarking technique using combinational spatial and frequency domains is presented. In order to correct rounding errors, a novel technique based on the genetic algorithm (GA) is developed. By separating medical images into Region of Interest (ROI) and non-ROI parts, higher compression rates can be achieved where the ROI is compressed by lossless compression and the non-ROI by lossy compression. The GA-based watermarking technique can also be considered as a fundamental platform for other fragile watermarking techniques. In order to simplify the selection and integrate different watermarking techniques, a novel adjusted-purpose digital watermarking is developed. In order to enlarge the capacity of robust watermarking, a novel robust high-capacity watermarking is developed. In steganographic system, a novel steganographic algorithm is developed by using GA to break the inspection of steganalytic system. In morphological processing, the GA-based techniques are developed to decompose arbitrary shapes of big binary structuring elements and arbitrary values of big grayscale structuring elements into small ones. The decomposition is suited for a parallel-pipelined architecture. The techniques can speed up the morphological processing and allow full freedom for users to design any type and any size of binary and grayscale structuring elements. In applications such as shortest path planning, a novel method is first presented to obtaining Euclidean distance transformation (EDT) in just two scans of image. The shortest path can be extracted based on distance maps by tracking minimum values. In order to record the motion path, a new chain-code representation is developed to allow forward and backward movements. By placing the smooth turning-angle constraint, it is possible to mimic realistic motions of cars. By using dynamically rotational morphology, it is not only guarantee collision-free in the shortest path, but also reduce time complexity dramatically. As soon as the distance map of a destination and collision-free codes have been established off-line, shortest paths of cars given any starting location toward the destination can be promptly obtained on-line

Chained segment offsetting for ray-based solid representations

International audienceWe present a novel approach to offset solids in the context of fabrication. Our input solids can be given under any representation: boundary meshes, voxels, indicator functions or CSG expressions. The result is a ray-based representation of the offset solid directly used for visualization and fabrication: We never need to recover a boundary mesh in our context. We define the offset solid as a sequence of morphological operations along line segments. This is equivalent to offsetting the surface by a solid defined as a Minkowski sum of segments, also known as a zonotope. A zonotope may be used to approximate the Euclidean ball with precise error bounds. We propose two complementary implementations. The first is dedicated to solids represented by boundary meshes. It performs offsetting by modifying the mesh in sequence. The result is a mesh improper for direct display, but that can be resolved into the correct offset solid through a ray representation. The major advantage of this first approach is that no loss of information – re-sampling – occurs during the offsetting sequence. However, it applies only to boundary meshes and cannot mix sequences of dilations and erosions. Our second implementation is more general as it applies directly to a ray-based representation of any solid and supports any sequence of erosion and dilation along segments. We discuss its fast implementation on modern graphics hardware. Together, the two approaches result in a versatile tool box for the efficient offsetting of solids in the context of fabrication

Using geometric algebra to interactively model the geometry of Euclidean and non-Euclidean spaces.

This research interprets and develops the 'conformal model of space' in a way appropriate for a graphics developer interested in the design of interactive software for exploring 2-dimensional non-Euclidean spaces. The conformal model of space extends the standard projective model – instead of adding just one extra dimension to standard Euclidean space, a second one is added that results in a Minkowski space similar to that of relativistic spacetime. Also, standard matrix algebra is replaced by geometric ( i.e. Clifford) algebra. The key advantage of the conformal model is that both Euclidean and non- Euclidean spaces are accommodated within it. Transformations in conformal space are generated by bivectors which are special elements of the geometric algebra. These induce geometric transformations in the embedded non Euclidean spaces. However, the relationship between the bivector generated transformations of the Minkowski modelling space and the geometric transformations they induce is extremely obscure. This thesis provides new analytical tools for determining the nature of this relationship. Their derivation was motivated by the need to successfully solve key implementation problems relating to navigation and in-scene mouse interaction. The analytic approaches developed not only successfully solved these problems but pointed the way to implementing other unplanned features. These include facilities for dynamically altering on-screen geometry as well as using multiple viewports to allow the user to interact with the same objects embedded in different geometries. These new analytical approaches could be powerful tools for solving future and as yet unforeseen implementation problems