2166869
Font recognition based on global texture analysis
In this paper, we describe a new texture analysis based approach towards font recognition. Existing methods are typically based on local features that often require connected components analysis. In our new method, we take the document as an image containing some special textures, and font recognition as texture identification. The method is content independent and involves no local feature analysis. Global features are extracted by texture analysis. We apply the well-established 2D Gabor filtering technique to extract such features and a weighted Euclidean distance classifier to fulfil the recognition task. Experiments are made using 6,000 samples of 24 frequently used Chinese fonts (6 typefaces combined with 4 styles) and very promising results are achieved.
1231228
Font Recognition Based on Global Texture Analysis
We describe a novel texture analysis-based approach toward font recognition. Existing methods are typically based on local typographical features that often require connected components analysis. In our method, we take the document as an image containing some specific textures and regard font recognition as texture identification. The method is content-independent and involves no detailed local feature analysis. Experiments are carried out by using 14000 samples of 24 frequently used Chinese fonts (six typefaces combined with four styles), as well as 32 frequently used English fonts (eight typefaces combined with four styles). An average recognition rate of 99.1 percent is achieved. Experimental results are also included on the robustness of the method against image degradation (e.g., pepper and salt noise) and on the comparison with existing methods.
11321791
A new face detection method based on shape information
Automatic detection of human faces is one of the most difficult problems in pattern recognition. In many practical applications (e.g. personal identification using photo-IDs), face images often have a simple background. In this paper, we propose a new method based on shape information. Our system can be very efficient for images with simple background. Input image is first enhanced by means of histogram equalization, followed by edge detection based on a multiple-scale filter. The extracted edges are then linked using a method based on an energy function. The face contour is finally extracted using the direction information of the linked edges. Experimental results are included to verify the effectiveness of this method. (C) 2000 Elsevier Science B.V. All rights reserved.
15339123
Utilizing jump flooding in image-based soft shadows
This paper studies the usage of the GPU as a collection of groups of related processing units, where each group communicates in some way to complete a computation efficiently and effectively. In particular, we use the GPU to perform jump flooding to pass information among groups of processing units in the design of two simple real-time soft shadow algorithms. These two algorithms are purely image-based in generating plausible soft shadows. Their computational costs depend mainly on the resolution of the shadow map or the screen. They run on an order of magnitude faster than existing comparable methods.
625121
A comprehensive high-level synthesis system for control-flow intensive behaviors
In this paper, we describe a comprehensive high-level synthesis system for control-flow intensive as well as data-dominated behaviors. We propose a new control-data flow graph model to preserve the parallelism inherent in the application, as well as to facilitate high-level synthesis. Our algorithm, which is based on an iterative improvement strategy, performs clock selection, scheduling, module selection, resource allocation and assignment simultaneously to fully derive the benefits of design space exploration at the behavior level. The system can be used to optimize area, power or energy, by selecting the cost function accordingly. Experimental results show that for energy-optimized designs, energy is reduced by up to 79.4% (an average of 42.2%), with an average of 24.8% area overhead, compared to area-optimized designs. For power-optimized designs, power is reduced by up to 70.8% (an average of 56.7%), with an average of 25.2% area overhead, compared to area-optimized designs. No Vdd scaling is performed to obtain the above results.
8559676
A simulation framework for energy-consumption analysis of OS-driven embedded applications
Energy consumption has become a major focus in the design of embedded systems (e.g., mobile computing and wireless communication devices). In particular, a shift of emphasis from hardware-oriented low-energy design techniques to energy-efficient embedded software design has occurred progressively in the past few years. To that end, various techniques have been developed for the design of energy-efficient embedded software. In operating system (OS)-driven embedded systems, the OS has a significant impact on the system's energy consumption directly (energy consumption associated with the execution of the OS functions and services), as well as indirectly (interaction of the OS with the application software). As a first step toward designing energy-efficient OS-based embedded systems, it is important to analyze the energy consumption of embedded software by taking the OS energy characteristics into account. To facilitate such studies, we present, in this work, an energy simulation framework that can be used to analyze the energy consumption characteristics of an embedded system featuring the embedded Linux OS running on the StrongARM processor. The framework allows software designers to study the energy consumption of the system software in relation to the application software, identify the energy hot spots, and perform design changes based on the knowledge of the OS energy consumption characteristics as well as application-OS interactions.
10936404
Affine invariant texture signatures
We develop a new approach for texture classification independent of affine transforms. Based on a spectral representation of texture images under affine transform, anisotropic scale invariant signatures of the orientation spectrum distribution are extracted. A peaks distribution vector (PDV) obtained on the distribution of these signatures captures texture properties invariant to affine distortion. The PDV is used to measure the similarity between textures. Experimental results show the efficiency of the PDV for affine invariant texture classification.
14857874
Anti-aliasing and Continuity with Trapezoidal Shadow Maps
This paper proposes a new shadow map technique termed trapezoidal shadow maps to calculate high quality shadows in real-time applications. To address the resolution problem of the standard shadow map approach, our technique approximates the eye's frustum as seen from the light with a trapezoid to warp it onto a shadow map. Such a trapezoidal approximation, which may first seem straightforward, is carefully designed to achieve the goal of good shadow quality for objects from near to far, and to address the continuity problem that is found in all existing shadow map approaches. The continuity problem occurs mainly when the shadow map quality changes significantly from frame to frame due to the motion of the eye or the light. This results in flickering of shadows. On the whole, our proposed approach is simple to implement without using complex data structures and it maps well to graphics hardware as shown in our experiments with large virtual scenes of hundreds of thousands to over a million of triangles.