scholarly journals Angle and Scale Invariant Template Matching for Handling Image Distortions

2018 ◽  
Vol 7 (2.24) ◽  
pp. 102
Author(s):  
Badrinaathan J ◽  
L N.B.Srinivas
Keyword(s):  
Template Matching ◽  
Histogram Equalization ◽  
Vital Role ◽  
Source Image ◽  
Image Patch ◽  
Scale Invariant ◽  
Matching Algorithm ◽  
Template Image ◽  
Computer Vision Applications

Template matching is a diagnostic approach for detecting a patch of a template image in a given source image. This plays a vital role in multitudinal computer vision applications. In this paper, we propose a methodology that makes the naive template matching algorithm scale and angle invariant during the image recognition process where the source and template is converted to gray scale which makes the technique enhance its proficiency. The proposed algorithm handles the arbitrary modulations of the image patch with respect to size and angle by an exhaustive search of all combinations of sizes are done along with populous combinations of angles. The images adapted are subjected to certain filtering and convolution methods which deepens the quality of the images which in turn assists in retrieving the features with accuracy. The image intensities are adjusted using histogram equalization to enhance the image contrast. These images are then subjected to perform template matching using normalized cross correlation to measure similarity between those two images.  

Research of an Improved Snail Image Recognition Method Based on Grayscale Template Matching

2013 ◽  
Vol 433-435 ◽  
pp. 700-704
Author(s):  
Yin E Zhang
Keyword(s):  
Template Matching ◽  
Source Image ◽  
Complex Environment ◽  
Recognition Method ◽  
Matching Method ◽  
Matching Accuracy ◽  
Matching Algorithm ◽  
Template Image ◽  
Traditional Algorithm ◽  
Template Selection

As the lack in the accuracy and speed of the template matching algorithm for the snail image in the complex environment, the snail source image and the template image have the appropriate scaling in order to improve their sizes in the traditional algorithm. The new algorithm avoids the very big and accurate characteristics about the snail images through shrinking the source images down. The grayscale template matching method is put forward based on the traditional template selection set to prevent that the error caused by human factors on the selected template, the redundancy between the templates is removed in a large extent, further the accuracy of the matching is improved, and the matching time is reduced greatly in the case of matching accuracy guarantee.

scholarly journals Image recognition in online monitoring of power equipment

2020 ◽  
Vol 17 (1) ◽  
pp. 172988141990083
Author(s):  
Guifeng Wu ◽  
Miao Yu ◽  
Wangwang Shi ◽  
Shengquan Li ◽  
Jiatong Bao
Keyword(s):  
Image Recognition ◽  
Template Matching ◽  
Online Monitoring ◽  
Source Image ◽  
Power Equipment ◽  
Target Image ◽  
Matching Algorithm ◽  
Matching Process ◽  
Abnormal State ◽  
Fast Recognition

The application of remote digital video surveillance and image recognition technology in online monitoring of power equipment is conducive to timely equipment maintenance and troubleshooting. In order to solve the problem of slow speed and large amount of computation of traditional template matching algorithm for power image recognition, a second template matching algorithm for fast recognition of target image is proposed in this article. Firstly, a quarter of the template data is taken and matched within a quarter of the source image, and a reasonable error threshold is given in the matching process. Then, the neighborhood of the minimum error point in rough matching is matched to get the final result. Finally, the algorithm is applied to identify the power equipment and detect the abnormal state of the power equipment. The experimental results show that the matching algorithm can not only accurately locate and identify power equipment and detect equipment faults, but also greatly improve the matching speed compared with other commonly used template matching algorithms.

scholarly journals Detection of Vehicles Number Plate Using Image Processing with Template matching Method

2019 ◽  
Vol 7 (1) ◽  
pp. 14-24
Author(s):  
Ivany Sarief ◽  
Harfin Yusuf Biu ◽  
Fajar Harismana ◽  
Sepryan Ismail Chandra
Keyword(s):  
Image Processing ◽  
Template Matching ◽  
Input Image ◽  
License Plate ◽  
Processing Unit ◽  
Matching Method ◽  
Capture Process ◽  
Matching Algorithm ◽  
Template Image ◽  
Parking System

To design a system in order to identify an object number plate for the Indonesian format, an initial system is designed, in the form of a vehicle licence plate recognition application using template matching method. The goal of this application is to be implemented to the parking system by identifying the number plate. This system uses the camera for the image capture process, by utilizing image processing technology with the matching correlation template method for recognition to produce a string value from the image. Before doing recognition process, First, the pre processing stage is performed on the input image which includes grayscale, binary, until the segmentation stage before the correlation / comparison process is carried out on the image of Template. The process that occure in the pre-processing unit done for some reason including to make the image lighter and less complex. This process will make the image easer to be processed and also to increase the proses speed of the system. Before aply template matching algorithm to the image output from segmentation process, the image has to be resized first to match the size of the template image stored in data base. This has to done so that the target image and the template image can be match directly with template matching algorithm.  The output of this system is a string value which is refer to the value of the license plate capture by camera used by the system. The problem that arises in the introduction process is how to identify various types of characters with various sizes and shapes so that the string value is the same as the text image. The average success rate of this application is 70% so that further research must be carried out so this system can be implemented into the parking system. Keyword : Image Processing, Template matching, Camera, Number Plate, Matlab

scholarly journals PENGENALAN IRIS MATA MENGGUNAKAN METODE TEMPLATE MATCHING CORRELATION

2019 ◽  
Vol 2 (2) ◽  
pp. 105
Author(s):  
Sayuti Rahman ◽  
Ulfa Sahira
Keyword(s):  
Correlation Coefficient ◽  
Programming Language ◽  
Template Matching ◽  
Matching Method ◽  
Processing Stage ◽  
Matching Algorithm ◽  
Template Image ◽  
Automatic Methods ◽  
System Success ◽  
Human Characteristic

Abstract - Biometrics is the study of automatic methods for recognizing humans based on one or more parts of the human body that are unique. One human characteristic that can be used is iris, iris features can be used as distinguishing characteristics with other individuals. The stage that the writer did to be able to recognize the iris pattern of someone's eye in a digital image was the pre-processing stage, the template saving stage and the matching stage. In this study the author applies the template matching method to store the image into a template image stored in the database and the algorithm correlation coefficient for the characteristic matching algorithm between template data and test data. The application is designed using the Matlab R2010a programming language. The results of testing 22 images obtained by the percentage of system success was 86.36%. Keywords - Iris, Template Matching, Correlation Coefficient

scholarly journals Comparative study of image enhancement techniques using histogram equalization on degraded images

2018 ◽  
Vol 7 (2.8) ◽  
pp. 468 ◽  
Author(s):  
Shalika Arora ◽  
Megha Agarwal ◽  
Veepin Kumar ◽  
Divya Gupta
Keyword(s):  
Image Processing ◽  
Comparative Study ◽  
Image Enhancement ◽  
Digital Image Processing ◽  
Digital Image ◽  
Histogram Equalization ◽  
Vital Role ◽  
Enhancement Technique ◽  
Degraded Images

Image Enhancement technique plays a vital role in digital image processing for making an image to be useful for various applications. This technique is used to improve the quality of degraded images.Usually, the degradation is not evenly spread throughout the image, but most of the time it varies from region to region. Our aim is to first identify the region where enhancement is required and improve that region without disturbing its neighbourhood which does not require any improvement. 

Identification of Location and Orientation for Terminal Blocks Based on Template Matching

2013 ◽  
Vol 561 ◽  
pp. 515-520
Author(s):  
Yu Xia Cui ◽  
Yang Li ◽  
Hua Jie Wang ◽  
Xian Lun Wang
Keyword(s):  
Template Matching ◽  
Vision System ◽  
Recognition Rate ◽  
Least Square Method ◽  
Least Square ◽  
Source Image ◽  
Centre Of Gravity ◽  
Gaussian Pyramid ◽  
Template Image ◽  
Real Time Application

A template matching method based on a vision system is proposed to get the location of terminal blocks. Gaussian pyramid decomposition is used to get the source image and template image samples, which will reduce the matching time and thus fulfill the requirement of real time application. The positioning screws used as mark points can be obtained by binarization, erosion, and dilation, and then the location of them can be worked out by the centre-of-gravity method. Finally, the location and the rotation angle of terminal blocks can be obtained with least square method. Experimental results show that this method is convenient to be operated with high recognition rate and efficiency.

Analysis of color Image Enhancement Using DWT, Wavelet Shrinkageand FHE Methods

2017 ◽  
Vol 7 (8) ◽  
pp. 56
Author(s):  
Ashish Dwivedi ◽  
Nirupma Tiwari
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Human Perception ◽  
Histogram Equalization ◽  
Wavelet Shrinkage ◽  
Visual Appearance ◽  
Enhancement Method ◽  
Fuzzy Histogram ◽  
Rgb Image

Image enhancement (IE) is very important in the field where visual appearance of an image is the main. Image enhancement is the process of improving the image in such a way that the resulting or output image is more suitable than the original image for specific task. With the help of image enhancement process the quality of image can be improved to get good quality images so that they can be clear for human perception or for the further analysis done by machines.Image enhancement method enhances the quality, visual appearance, improves clarity of images, removes blurring and noise, increases contrast and reveals details. The aim of this paper is to study and determine limitations of the existing IE techniques. This paper will provide an overview of different IE techniques commonly used. We Applied DWT on original RGB image then we applied FHE (Fuzzy Histogram Equalization) after DWT we have done the wavelet shrinkage on Three bands (LH, HL, HH). After that we fuse the shrinkage image and FHE image together and we get the enhance image.

Image Quality Enhancing by Efficient Histogram Equalization

2014 ◽  
Vol 2 (2) ◽  
pp. 47-58
Author(s):  
Ismail Sh. Baqer
Keyword(s):  
Image Quality ◽  
Contrast Enhancement ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Gray Level ◽  
Signal To Noise ◽  
Squared Error ◽  
Noise Ratio

A two Level Image Quality enhancement is proposed in this paper. In the first level, Dualistic Sub-Image Histogram Equalization DSIHE method decomposes the original image into two sub-images based on median of original images. The second level deals with spikes shaped noise that may appear in the image after processing. We presents three methods of image enhancement GHE, LHE and proposed DSIHE that improve the visual quality of images. A comparative calculations is being carried out on above mentioned techniques to examine objective and subjective image quality parameters e.g. Peak Signal-to-Noise Ratio PSNR values, entropy H and mean squared error MSE to measure the quality of gray scale enhanced images. For handling gray-level images, convenient Histogram Equalization methods e.g. GHE and LHE tend to change the mean brightness of an image to middle level of the gray-level range limiting their appropriateness for contrast enhancement in consumer electronics such as TV monitors. The DSIHE methods seem to overcome this disadvantage as they tend to preserve both, the brightness and contrast enhancement. Experimental results show that the proposed technique gives better results in terms of Discrete Entropy, Signal to Noise ratio and Mean Squared Error values than the Global and Local histogram-based equalization methods

Cytoprotective Agents to Avoid Chemotherapy Induced Sideeffects on Normal Cells: A Review

2019 ◽  
Vol 19 (10) ◽  
pp. 765-781
Author(s):  
Seema Rohilla ◽  
Harish Dureja ◽  
Vinay Chawla
Keyword(s):  
Adverse Effects ◽  
Anticancer Agents ◽  
Therapeutic Index ◽  
Chemotherapeutic Agents ◽  
Vital Role ◽  
Normal Cells ◽  
Normal Tissues ◽  
Organ Specific ◽  
Delay In Treatment

Anticancer agents play a vital role in the cure of patients suffering from malignancy. Though, the chemotherapeutic agents are associated with various adverse effects which produce significant toxic symptoms in the patients. But this therapy affects both the malignant and normal cells and leads to constricted therapeutic index of antimalignant drugs which adversely impacts the quality of patients’ life. Due to these adversities, sufficient dose of drug is not delivered to patients leading to delay in treatment or improper treatment. Chemoprotective agents have been developed either to minimize or to mitigate the toxicity allied with chemotherapeutic agents. Without any concession in the therapeutic efficacy of anticancer drugs, they provide organ specific guard to normal tissues.

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