HAUSDORFF DERIVATIVE LAPLACIAN OPERATOR FOR IMAGE SHARPENING

Image sharpening based on the partial differential equations plays an important role in the fields of image processing. It is an effective technique to clear and sharpen image features, and provides a higher resolution for the subsequent processing. This paper makes the first attempt to employ the Hausdorff derivative Laplacian operator to sharpen the images. In terms of the visual quality of details, contours and edges, the original images and noisy images were sharpened by using an appropriate Hausdorff derivative order. Numerical results indicate that the Hausdorff derivative Laplacian operator outperforms the high-pass filtering, the Roberts operator and the traditional integer-order Laplacian operator. In comparison with the existing methods for the image sharpening, the proposed new methodology could be considered as a competitive alternative.

On the Use of Edge Features and Exponential Decaying Number of Nodes in the Hidden Layers for Handwritten Signature Recognition

Handwritten signatures are playing an important role in finance, banking and education and more because it is considered the “seal of approval” and remains the most preferred means of authentication. In this paper, an offline handwritten signature authentication algorithm is proposed using the edge features and deep feedforward neural network (DFNN). The number of hidden layers in DFNN is configured to be at least one layer and more. In this paper, an exponential decaying number of nodes in the hidden layers was proposed to achieve better recognition rate with reasonable training time. Of the six edge algorithms evaluated, Roberts operator and Canny edge detectors were found to produce better recognition rate. Results showed that the proposed exponential decaying number of nodes in the hidden layers outperform other structure. However, more training data was required so that the proposed DFNN structure could have more efficient learning.

License Plate Recognition System Design

The license plate recognition system is an important part of modern traffic management. application which is very extensive. In this paper, a method to achieve three main modules split from the image pre-processing, license plate location and character. Image pre-processing module of this article is to image gray and step by Roberts operator edge detection. License plate positioning and segmentation using mathematical morphology is used to determine the license plate location method, and then use the license plate color information of color segmentation method to complete the license plate parts division. This article is to research its main part and use MATLAB to do the image processing simulation.

Seeds Microscopic Image Edge Detection Based on the Clustering Method and Applied in Andriod Platform

Sobel, Roberts operator is derived based on the differential. As a result of the template and fixed threshold value, it lacks adaptability. Median filter on images of the collected cardiac seeds maturity, use split clustering algorithm on cardiac seeds maturity for the first image gradient value clustering, condensed cluster on the result of the first split the clustering results, then secondly division cluster, and finally work out the image edge based on the second clustering results and realize on the FPGA implementation. At last the method is Applied in Andriod Platform. The experimental results show that it is more delicate to use the hierarchical clustering algorithm to detect the edge and it has stronger ability to suppress noise.

Algorithm Research of Stone Contour Extraction Based on Computer Vision Theory

Stone contour extraction is the major step and key process. It plays a crucial role in real-time optimizing irregular stone cutting and the layout of the material. It is not only important to improve production efficiency and the utilization of the stone, but also to save stone resources. Based on computer vision, this paper studies the algorithm of stone contour extraction. By analyzing image enhancement and filtering, it puts forward the image preprocessing methods of grayscale and median filtering; After comparing the Roberts operator, Sobel operator, Prewitt operator and Laplacian comparison, it can be found that Sobel operator can detect more subtle edge and the detected edge is also great brightness. So the visual effect is more clear. It has the certain inhibition for isolated noise. So Sobel operator of edge detection is used to extract target contour stone in this paper.

A Method Based on the Morphology of Lead-Free Solder Powder Adhesive Particle Segmentation

Three kinds of lead-free soldering tin powder particles produced by means of ultrasonic vibration atomization were studied in this paper. For tin powder particles had higher edge angle and more irregular shape which were the two most key elements that may influence the quality of soldering paste, aspect ratio and fractal dimension of those particles were treated as the facts that could reflect the morphology of soldering tin powder particles. Geometrical projected images of those particles were acquired by optical microscope and image computing were processed by morphologic method. Since particles adhesion phenomenon often occurred in actual image processing of soldering tin powder particles, Roberts operator was used for edge detection and in the meantime, Erosion method and Dilation method in morphological operation were applied to segment those adhesive particles. It was shown that the morphologic method proposed in this paper could be applied to segment those images of adhesive particles.

Application of Petrochemical Heat Equipments' State Inspection Based on the Edge Detection of Infrared Image Segmentation

According to the problem of petrochemical heat equipment status inspection and fault diagnosis, a method based on edge detection of infrared image segmentation was presented studying the infrared image segmentation based on edge detection and combining Roberts operator into best threshold segmentation method to do simulation of buoyant, medium and heavy damaged equipments. Experimental result shows that edge detection operator of best threshold value has ideal effects to the image edge extraction's target area of thermal infrared equipment.

Research and Analysis of Edge-Detection of Digital Images

Edge-detection is the basic characteristic of images. Edge-detection plays an important role in computer vision and image analysis, it is the key link of image analysis and recognition. In this paper, we mainly analyze several edge-detection operators, research the processing results. The edge-detection operators mainly include Roberts operator, Prewitt operator, Sobel operator, Canny operator and LoG operator. Finally we discuss the advantage and disadvantage of the edge-detection operators.