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Image edge detection plays an important role in the system of computer vision. Wavelet is a powerful tool in image processing and has wide application to edge detection for its multiscale characteristic. Based on wavelet modulus maximum edge detection algorithm, an improved method is proposed in this paper, which gives an automatic determination function of eliminateing noise threshold by using the...
The plate parameter measurement method can be applied to industrial intelligent control. It not only reduces the cost of plate parameter measurement, but also improves the accuracy and efficiency. Based on the practical application and research of object extraction on plate image, the paper proposes a kind of plate parameter measurement method based on ISL (Image Segmentation and Thinning) algorithm...
Vision-based driver assistance requires basic vision modules for stereo analysis or optic flow calculation. Driving situations change frequently, and methods need to be evaluated in the real world. The paper proposes ways for evaluating optic flow techniques by using estimated geometries for surrounding buildings or 'road furniture'. It demonstrates the value of such an evaluation by discussing four...
In order to quickly and exactly extract the subpixel image edge, a new method of subpixel image edge based on Fourier-Mellin moment is proposed. Firstly all possible edge points were detected quickly with using Fourier-Mellin moment operator with mask size of 3×3, secondly a Fourier-Mellin moment operator with mask size of 7×7 was used to relocate the edge with subpixel accuracy. Experiment results...
A lag-free CMOS image sensor (CIS) with Constant-Residue Reset (CRR) operation is presented in this paper. It effectively eliminates image lag effect caused by the channel doping profile variation of transfer transistor and non-optimized pixel layout in the 4T-pixel. A prototype 160×120 CMOS imager has been designed and fabricated in 0.18um 1P4M CIS process. The experimental results demonstrated that...
This paper comes within the framework of designing a recognition system of mathematical symbols. Through this, we first recall the general process of recognition of mathematical symbols while focusing on the description of our method for segmentation of offline mathematical symbols. Our goal is to detect, extract and segment the different symbols of mathematical expression. This expression will be...
Fuzzy C-Means (FCM) algorithm is the most popular method used in image segmentation for clustering because it has robust characteristics for ambiguity and can retain much more information than hard segmentation methods. Although the conventional FCM algorithm works well on most noise-free images, it is very sensitive to noise and other imaging artifacts, since it does not consider any information...
In this paper a new, faster approach which is different from all the other conventional image vectorization techniques. Using canny edge detection we are able to find the sharp edges in the image and the assigning shades to each identifiable segment using random colour extraction from the original image. Finally mapping the colour blobs with the SVG Schema and generating a scalable vector image. This...
Image segmentation is an important branch of computer vision. Its aim is to extract meaningful lying in objects images, either by dividing images into contiguous semantic regions, or by extracting one or several objects more specific in images, such as medical structures. In general, image segmentation task is very difficult to achieve it since natural images are diverse, complex and the way we perceive...
There are many websites specially designed for mobile phones. Some hackers write automated programs to abuse these website services and waste the website resources. Therefore, it is necessary to distinguish between human users and computer programs. Methods known for achieving this are known as CAPTCHA (Completely Automated Public Turing test to tell Computers and Human Apart). CAPTCHA methods are...
The CMOS image sensors are achieving a growing presence in today's mobile applications as the industry acknowledges the advances of the CMOS-based technology and its scaling possibilities. The roadmap recently unveiled for CMOS Image Sensor is announcing ever smaller pixels, after 1.4μm pixel pitch, demos with a pitch of 1.1μm were presented, and it also announces the future generation of pixels with...
Background Modeling is the normal method on the moving objects detection, it plays a key role in the moving objects detection and tracking, the Gaussian mixture model is one of the most successful methods on the detection. But it converges slowly in the complex scene. This paper proposes a new method named “additive increase” and the “additive decrease” to adjust the weight of the matched distributions...
Melanoma can be cured if it is detected early, so early diagnosis is very important in dermatological practice today. Early and non-invasive diagnosis of melanomas can be done by accurate image segmentation of skin lesions. The medical images, while acquisition are generally bound to contain noise. This paper proposes a robust and efficient image segmentation algorithm using LOG edge detector to extract...
Complementary metal oxide semiconductor (CMOS) image sensors are more compatible than charge coupled devices (CCDs) for lab-on-a-chip platforms due to their inherited advantages. However, without the noise reduction circuits, CMOS technology wouldn't be able to compete with CCDs. Today, correlated double sampling circuits (CCDs) are used in all CMOS imagers in order to remove the reset noise and the...
In this paper, a non-contact approach to roundness measurement using machine vision is proposed. A test-rig and computer algorithm are developed to realised the approach. The computer algorithm employs minimum zone circle MZC technique to measure the roundness deviation. High contrast and good quality image segmentation is produced with the developed image processing algorithm technique. Camshaft...
Image restoration is the process of recovering the original image from the degraded image. Aspire of the project is to restore the blurred/degraded images using Blind Deconvolution algorithm. The fundamental task of Image deblurring is to de-convolute the degraded image with the PSF that exactly describe the distortion. Firstly, the original image is degraded using the Degradation Model. It can be...
Ultrasound imaging is a widely used and safe medical diagnostic technique, due to its noninvasive nature, low cost, real time imaging. However the usefulness of ultrasound imaging is degraded by the presence of signal depended noise known as speckle.. The speckle pattern depends on the structure of the image tissue and various imaging parameters. There are two main purposes for speckle reduction in...
Spectral unmixing is commonly used in the solar-reflective spectral regime to find materials down to abundances (`pixel fill factors' (PFFs) or `target fractions') of (typically) ~10%. However, little is known about whether such spectral unmixing applies in the long-wavelength-infrared (LWIR) spectral regime (designated herein as the “thermal” region). The first part of this paper discusses a numerical...
Gel electrophoresis (GE) is an important tool in genomic analysis. It is a process of DNA, RNA and protein molecules separation using electric field applied to a gel matrix. This paper describes the image processing techniques applied on GE image to segment the bands from their background. Numerous pre-processing steps are applied on the image prior to the segmentation technique for the purpose of...
In this paper we propose a denoising method under the powerful framework-non local means (NL-means), in conjunction with regression analysis. First, the conception and development of NL-means is proposed. Second, an image important area map (IIAM) is calculated for the protection of edge and structure regions during denoising. Therefore, improved version of NL-means is carried out, which uses a novel...
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