Search results for "edge detection"
showing 10 items of 43 documents
Frequency spike encoding using Gabor-like receptive fields
2014
Abstract Spiking Neural Networks (SNN) are a popular field of study. For a proper development of SNN algorithms and applications, special encoding methods are required. Signal encoding is the first step since signals need to be converted into spike trains as the primary input to an SNN. We present an efficient frequency encoding system using receptive fields. The proposed encoding is versatile and it can provide simple image transforms like edge detection, spot detection or removal, or Gabor-like filtering. The proposed encoding can be used in many application areas as image processing and signal processing for detection and classification.
Design of an image processing integrated circuit for real time edge detection
2003
Presents the design of a real time image processing micro-system to detect defects on manufacturing products. The analysis method is based on an edge detection algorithm (differential operators) to select the information related to the structure of the objects present in the image. The edge calculation function has been integrated in a standard cell circuit using a CMOS 1.5 mu m process. The ASIC has been implemented and tested in an image processing microsystem with a CCD camera. Results show an improvement of performances (speed, noise, size reduction system characterization, etc. . .) in comparison with the first prototypes (software implementation and printed board with standard compone…
2014
For locating inaccurate problem of the discrete localization criterion proposed by Demigny, a new criterion expression of “good localization” is proposed. Firstly, a discrete expression of good detection and good localization criterion of two dimension edge detection operator is employed, and then an experiment to measure optimal parameters of two dimension Canny's edge detection operator is introduced after. Moreover, a detailed performance comparison and analysis of two dimension optimal filter obtained via utilizing tensor product for one dimension optimal filter are provided which can prove that least square support vector regression (LS-SVR) is a smoothness filter and give the construc…
An Automatic Three-Dimensional Fuzzy Edge Detector
2009
Three-dimensional object analysis is of particular interest in many research fields. In this context, the most common data representation is boundary mesh, namely, 2D surface embedded in 3D space. We will investigate the problem of 3D edge extraction, that is, salient surface regions characterized by high flexure. Our automatic edge detection method assigns a value, proportional to the local bending of the surface, to the elements of the mesh. Moreover, a proper scanning window, centered on each element, is used to discriminate between smooth zones of the surface and its edges. The algorithm does not require input parameters and returns a set of elements that represent the salient features …
Multi-feature Counting of Dense Crowd Image Based on Multi-column Convolutional Neural Network
2020
The crowd counting task is an important research problem. Now more and more people are concerned about safety issues. When the population density reaches a very high peak, the population density counts, the alarm is sent out, and the crowds are diverted. The trampling of the Shanghai New Year’s stampede will not happen again. The final density map is produced by two steps: at first, extract feature maps from multiple layers, and then adjust their output so that they are all the same size, all these resized layers are combined into the final density map. We also used texture features and target edge detection to reduce the loss of density map detail to better integrate with our convolutional…
Real-time implementation of counting people in a crowd on the embedded reconfigurable architecture on the unmanned aerial vehicle
2020
The crowd counting task is an important research problem. Now more and more people are concerned about safety issues. Considering the scenario of a crowded scene: a population density system analyzes the crowds and triggers a warning to divert the crowds when their population density exceeds a normal range. With such a system, the incident of the Shanghai New Year's stampede will not happen again. The most difficult problem of population counting at present: On the one hand, in the densely populated area, how to make the model distinguish human head features more finely, such as head overlap. The second aspect is to find a small-scale local head feature in an image with a wide range of popu…
Learning-based multiresolution transforms with application to image compression
2013
In Harten's framework, multiresolution transforms are defined by predicting finer resolution levels of information from coarser ones using an operator, called prediction operator, and defining details (or wavelet coefficients) that are the difference between the exact and predicted values. In this paper we use tools of statistical learning in order to design a more accurate prediction operator in this framework based on a training sample, resulting in multiresolution decompositions with enhanced sparsity. In the case of images, we incorporate edge detection techniques in the design of the prediction operator in order to avoid Gibbs phenomenon. Numerical tests are presented showing that the …
High Level Modeling and Hardware Implementation of Image Processing Algorithms Using XSG
2019
International audience; Design of Systems-on-Chip has become very common especially with the remarkable advances in the field of high-level system modeling. In recent years, Matlab also offers a Simulink interface for the design of hardware systems. From a high-level specification, Matlab provides self-generation of HDL codes and/or FPGA configuration codes while providing other benefits of easy simulation. In addition, a large part of the Systems-on-Chip use at least one image processing algorithm and at the same time border detection is one of the most used algorithms. This paper presents a study and a hardware implementation of various algorithms of borders detection realized under Xilin…
Randomized Hough Transform for Ellipse Detection with Result Clustering
2005
Our research is focused on the development of robust machine vision algorithms for pattern recognition. We want to provide robotic systems the ability to understand more on the external real world. In this paper, we describe a method for detecting ellipses in real world images using the randomized Hough transform with result clustering. A preprocessing phase is used in which real world images are transformed - noise reduction, greyscale transform, edge detection and final binarization - in order to be processed by the actual ellipse detector. The ellipse detector filters out false ellipses that may interfere with the final results. Due to the fact that usually more "virtual" ellipses are de…
FAST EDGE-FILTERED IMAGE UPSAMPLING.
2011
We present a novel edge preserved interpolation scheme for fast upsampling of natural images. The proposed piecewise hyperbolic operator uses a slope-limiter function that conveniently lends itself to higher-order approximations and is responsible for restricting spatial oscillations arising due to the edges and sharp details in the image. As a consequence the upsampled image not only exhibits enhanced edges, and discontinuities across boundaries, but also preserves smoothly varying features in images. Experimental results show an improvement in the PSNR compared to typical cubic, and spline-based interpolation approaches.