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Feature extraction is an essential part in applications that require computer vision to recognize objects in an image processed. To extract the features robustly, feature extraction algorithms are often very demanding in computation so that the performance achieved by pure software is far from real-time. Among those feature extraction algorithms, scale-invariant feature transform (SIFT) has gained...
This paper presents the use of local oriented energy features for real-time object tracking on embedded vision systems. Local oriented energy features are extracted using complex Gabor filters. Filtering is carried out across multiple channels with different frequencies and orientations. The effectiveness of the chosen feature set is tested using a mean-shift tracker. Our experiments show that adding...
In view of the increasing demand of recognition system for paper currency number, to develop a type of number recognition system based on CIS and DSP. The hardware is composed of CIS and DSP which control image acquisition and process. The software is composed of image acquisition, character correction and recognition. To recognize character with noise pollution rapidly and accurately, a novel approach...
Real-time video enhancement is generally achieved using costly specialized hardware that have specific functions and outputs. Commercial off-the-shelf hardware, such as desktop computers with Graphics Processing Units (GPUs), are also commonly used as cost effective solutions for real-time video processing. In the past, the limitations in computer hardware meant that real-time video enhancement was...
We present a real-time multi-sensor architecture for video-based pedestrian detection used within a road side unit for intersection assistance. The entire system is implemented on available PC hardware, combining a frame grabber board with embedded FPGA and a graphics card into a powerful processing network. Giving classification performance top priority, we use HOG descriptors with a Gaussian kernel...
Image segmentation is an important technique in the area of image processing with wide applications in medicine, remote sensing to mention a few. A lot of research work is in progress in various areas resulting in many computationally efficient algorithms. There are conventional as well as improvised segmentation algorithms depending on the application. The choice of the technique in most cases depends...
In this paper, a new method to compute the image histogram is presented, along with the image maximum and minimum values. It is intended for highly parallel architectures such as the ones found in focal plane processors (FPP). This new approach exploits this parallelism relying on the privatization technique to avoid the memory collision problem, while the bin frequency is obtained through image bitwise...
A novel adaptive image enhancement technique based on image characteristic is proposed in this paper. At first, the spatial high-pass filter (the Laplace filter) is applied to the original image data. Then, the first-order classifying of the image is employed on the basis of the specification of the output of the Laplace filter. The low-pass filter is applied to smooth the image for the high threshold...
Pedestrian recognition on embedded systems is a challenging problem since accurate recognition requires extensive computation. To achieve real-time pedestrian recognition on embedded systems, we propose hardware architecture suitable for HOG feature extraction, which is a popular method for high-accuracy pedestrian recognition. To reduce computational complexity toward efficient hardware architecture,...
Co-occurrence histograms of oriented gradients (CoHOG) is a powerful feature descriptor for pedestrian detection. However, its calculation cost is large because the feature vector for the CoHOG descriptor is very high-dimensional. In this paper, in order to achieve real-time detection on embedded systems, we propose a novel hardware architecture for the CoHOG feature extraction. Our architecture exploits...
A simple image enhancement technique based upon evolvable hardware is presented. Improving visual appearance is achieved by evolved histogram stretching transformation (evolved circuit). The performance is compared with the classical histogram equalization method using traditional measures of enhancement. Experimental results will be presented to show that the proposed technique offers better performance...
Real time object tracking finds its applications in diverse fields. An online embedded system for image tracking should be fast, accurate, robust and efficient. This paper presents a hardware based architecture and implementation of an image coprocessor on FPGA using Verilog hardware description language. The core concept is to ensure a fast and memory efficient dedicated hardware which could increase...
In this paper we introduce a reversible data hiding algorithm for medical images and its hardware implementation. Using the advantages of some proved methods and the characteristics of radiological medical images we obtain a large embedding capacity with minimum distortion of the original image using an easy control for recovering the hidden data and the original image. Moreover, in order to speed...
This paper presents a face detection hardware architecture which is based on a newly proposed algorithm using cascaded classifiers with vector angle similarity measurement between the investigated image and the face/non-face centroids. The proposed system is composed of three major modules: Best fit plane removal unit, Histogram equalization unit, and cascaded classification unit. Comprehensive optimization...
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