scholarly journals Wavelets assisted fuzzy edge refinement

2014 ◽  
Vol 14 (2) ◽  
pp. 5409-5418
Author(s):  
Kumud Saxena
Keyword(s):  
Feature Extraction ◽  
Object Recognition ◽  
Edge Detection ◽  
Image Enhancement ◽  
Experimental Results ◽  
Edge Enhancement ◽  
Processing Step ◽  
Edge Detectors ◽  
Novel Algorithm

Image enhancement is a crucial pre-processing step to be performed for various applications where object recognition, identification, verification is required. Among various image enhancement methods, edge enhancement has taken its importance as it is widely used for understanding features in an image. Several types of edge detectors are available for certain types of edges. If edges are enhanced and clear, the reliability for feature extraction increases. The Quality of edge detection can be measured from several criteria objectively. In this paper, a novel algorithm for edge enhancement has been proposed for multiple types of images. The features can be extracted clearly by using this method. For comparison purpose Roberts, Sobel, Prewitt, Canny, and Log edge operators are used and their results are displayed. Experimental results demonstrate the effectiveness of the proposed approach.

scholarly journals Contour Detection for Fibre of Preserved Szechuan Pickle Based on Dilated Convolution

2019 ◽  
Vol 9 (13) ◽  
pp. 2684 ◽  
Author(s):  
Hongyang Li ◽  
Lizhuang Liu ◽  
Zhenqi Han ◽  
Dan Zhao
Keyword(s):  
Edge Detection ◽  
State Of The Art ◽  
Contour Detection ◽  
Experimental Results ◽  
Contour Method ◽  
Class Differences ◽  
Dilated Convolution ◽  
The Mean ◽  
Art Performance

Peeling fibre is an indispensable process in the production of preserved Szechuan pickle, the accuracy of which can significantly influence the quality of the products, and thus the contour method of fibre detection, as a core algorithm of the automatic peeling device, is studied. The fibre contour is a kind of non-salient contour, characterized by big intra-class differences and small inter-class differences, meaning that the feature of the contour is not discriminative. The method called dilated-holistically-nested edge detection (Dilated-HED) is proposed to detect the fibre contour, which is built based on the HED network and dilated convolution. The experimental results for our dataset show that the Pixel Accuracy (PA) is 99.52% and the Mean Intersection over Union (MIoU) is 49.99%, achieving state-of-the-art performance.

Comparison of Thresholding and Edge Detection Segmentation Techniques

2013 ◽  
Vol 860-863 ◽  
pp. 2783-2786
Author(s):  
Yu Bing Dong ◽  
Hai Yan Wang ◽  
Ming Jing Li
Keyword(s):  
Image Segmentation ◽  
Root Mean Square Error ◽  
Edge Detection ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Experimental Results ◽  
Mean Square ◽  
Segmentation Method ◽  
Segmentation Algorithms

Edge detection and thresholding segmentation algorithms are presented and tested with variety of grayscale images in different fields. In order to analyze and evaluate the quality of image segmentation, Root Mean Square Error is used. The smaller error value is, the better image segmentation effect is. The experimental results show that a segmentation method is not suitable for all images segmentation.

scholarly journals An Extensive Review on Image Segmentation Techniques

2021 ◽  
Vol 1 (2) ◽  
pp. 1-5
Author(s):  
Kamlesh Sharma ◽  
Nidhi Garg
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Edge Detection ◽  
Frequency Domain ◽  
Image Enhancement ◽  
Digital Images ◽  
Extensive Review ◽  
Current Image ◽  
Segmentation Image

Image processing is the use of algorithms to perform various operations on digital images. The techniques that are explained further are image segmentation and image enhancement. Image Segmentation is a method to partition an image into multiple segments, to change the presentation of an image into something more meaningful and easier to analyze. The current image segmentation techniques include region-based segmentation and edge detection segmentation. Image Enhancement is the process of improving the quality of image. Under this section there are two broad divisions- Spatial Domain Technique and Frequency Domain Technique.

Study on Shape Recognition Based on Contour

2014 ◽  
Vol 644-650 ◽  
pp. 4240-4243
Author(s):  
Wei Zhang
Keyword(s):  
Feature Extraction ◽  
Object Recognition ◽  
Fourier Transformation ◽  
Recursive Algorithm ◽  
Shape Recognition ◽  
Experimental Results ◽  
Discrete Fourier Transformation ◽  
Object Contour ◽  
Important Character

Shape is the inherence characteristic of an object in the image, and it is the important character used for the object recognition. So it is significant for object recognition based on shape. This paper presents a contour-based method of feature extraction and shape recognition. First the object contour is translated into a 1-D contour curve. Secondly the curve is smoothed to restrain the noise. The number of peaks of the curve is achieved as well as the areas which contained between adjacent peak-valley, then the latter is followed by Discrete Fourier Transformation (DFT). Then two kinds of features ate extracted which are invariant to translation, scaling and rotation transformations. By using the features, a two-stake recursive algorithm for recognition is proposed. Experimental results show that this method is simple and efficient.

scholarly journals Image Enhancement by Frequency Analysis

2018 ◽  
Vol 228 ◽  
pp. 02008
Author(s):  
Chen Yao ◽  
Yan Xia ◽  
Jiamin Zhu
Keyword(s):  
Image Enhancement ◽  
Frequency Analysis ◽  
Linear Mapping ◽  
Experimental Results ◽  
Image Mapping ◽  
Enhancement Factors ◽  
Central Energy ◽  
Enhancement Algorithm

Because of lighting or the quality of CMOS/CCD, poor images are often gained, which greatly affect subjective observation. Image enhancement can improve the contrast of poor image. In our paper, we propose a new image enhancement algorithm based on frequency analysis. A central energy of FFT is utilized for computation of image enhancement factors. A linear mapping is used for image mapping. Finally, some experimental results are shown for illustration of our algorithm advantage.

Novel Compact Genetic Algorithm for WTA Problem

2012 ◽  
Vol 239-240 ◽  
pp. 1437-1441 ◽  
Author(s):  
Zhen Liu ◽  
Yun An Hu
Keyword(s):  
Genetic Algorithm ◽  
Experimental Results ◽  
The Novel ◽  
Simple Genetic Algorithm ◽  
Exchange Information ◽  
Compact Genetic Algorithm ◽  
Two Populations ◽  
Novel Algorithm ◽  
Better Than

The paper proposed a novel compact genetic algorithm which is named as pseudo-parallel compact genetic algorithm. There are two populations in the process of evolution, and the two subpopulation can exchange information between each other. The experimental results show that the novel algorithm performs better than simple genetic algorithm. Then it is used to solve weapon target allocation (WTA) problem, and the simulation result shows that it is more efficient comparing with other methods. Because the compact genetic algorithm is easy to operate and take up less memory, so the algorithm exhibit a better quality of solution and the required less time than before.

scholarly journals An Extensive Review on Image Segmentation Techniques

2021 ◽  
pp. 1-5
Author(s):  
Dr. Kamlesh Sharma ◽  
◽  
Nidhi Garg ◽  
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Edge Detection ◽  
Frequency Domain ◽  
Image Enhancement ◽  
Digital Images ◽  
Extensive Review ◽  
Current Image ◽  
Segmentation Image

Image processing is the use of algorithms to perform various operations on digital images. The techniques that are explained further are image segmentation and image enhancement. Image Segmentation is a method to partition an image into multiple segments, to change the presentation of an image into something more meaningful and easier to analyze. The current image segmentation techniques include region-based segmentation and edge detection segmentation. Image Enhancement is the process of improving the quality of image. Under this section there are two broad divisions- Spatial Domain Technique and Frequency Domain Technique.

Local Statistic Enhancement of Digital Image Based on Genetic Algorithm

2013 ◽  
Vol 427-429 ◽  
pp. 1836-1840 ◽  
Author(s):  
Yong Zhuo Wu ◽  
Zhen Tu ◽  
Lei Liu
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Image Enhancement ◽  
Digital Image Processing ◽  
Digital Image ◽  
Experimental Results ◽  
Computer Application ◽  
Novel Method ◽  
New Research

Iamge repair using the digital image processing technology has become a new research point in computer application. A novel method of local statistic enhancement based on genetic algorithm is proposed in this paper for the image enhancement. The modified amplified function are used as the jugement criterion, and the optimal paremeters are searched by the genetic algorithm. Experimental results show that the quality of images is improved dramatically by using this method.

scholarly journals Development and Implementation of AUV for Data Acquisition and Image Enhancement

2020 ◽  
Vol 9 (4) ◽  
pp. 2088-2093
Keyword(s):  
Light Intensity ◽  
Edge Detection ◽  
Image Enhancement ◽  
Visual Observation ◽  
Low Light ◽  
Canny Edge Detection ◽  
Underwater Environment ◽  
Web Camera ◽  
Canny Edge

In our proposed work, the developed Acoustic Unmanned Vehicle(AUV) moves in the direction of up/down. In general AUV is mainly used to for visual observation of the underwater environment by using a web camera. The acquired data from the AUV was preprocessed and the same image used for enhancement.. In this project, the image enhancement alogrithms has been implemented and the same has been computed for Canny Edge Detection, Hue, Luma and Saturation. From these computed results, we are able to enhance the quality of images for the conditions like low depth, low light intensity and color contrasting has been achieved using LABVIEW.

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