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 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 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 Stereo Matching Based on HALCON

2013 ◽  
Vol 415 ◽  
pp. 361-364
Author(s):  
Hui Yu Xiang ◽  
Zhe Li ◽  
Jia Jun Huang ◽  
Baoan Han
Keyword(s):  
Image Matching ◽  
Stereo Matching ◽  
Vision System ◽  
Difficult Problem ◽  
Matching Method ◽  
Matching Accuracy ◽  
Matching Algorithm ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Matching Window

Binocular stereo matching is a hot and difficult problem in machine vision. In this paper, based on the matching method of Halcon which is visual software perform image matching. First, performing binocular stereo vision system calibration, based on the calibration results acquired the epipolar standard geometric structure. Then, image matching researched under this structure. At last, using ncc matching algorithm, through comparing the different parameters matching window obtain ideal match results. Experiments prove that this method not only can effectively shorten matching time, but also can achieve higher matching accuracy.

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 Parking Space Recognition Method Based on Parking Space Feature Construction in the Scene of Autonomous Valet Parking

2021 ◽  
Vol 11 (6) ◽  
pp. 2759
Author(s):  
Shidian Ma ◽  
Weifeng Fang ◽  
Haobin Jiang ◽  
Mu Han ◽  
Chenxu Li
Keyword(s):  
Template Matching ◽  
Recognition Algorithm ◽  
Feature Construction ◽  
Parking Space ◽  
Light Conditions ◽  
Recognition Method ◽  
Matching Algorithm ◽  
Information Interaction ◽  
Similarity Calculation ◽  
Space Recognition

At present, the realization of autonomous valet parking (AVP) technology does not achieve information interaction between the parking spaces and vehicles, and accurate parking spaces information perception cannot be obtained when the accuracy of the search is not precise. In addition, when using the camera vision to identify the parking spaces, traditional parking space features such as parking lines and parking angles recognition are susceptible to light and environment. Especially when the vehicle nearby partially occupies the parking space to be parked, it is not easy to determine whether it is a valid empty parking space. This paper proposes a parking space recognition method based on parking space features in the scene of AVP. By constructing the multi-dimensional features containing the parking space information, the cameras are used to extract features’ contour, locate features’ position and recognize features. In this paper, a new similarity calculation formula is proposed to recognize the stained features through template matching algorithm. According to the relative position relationship between the feature and parking space, the identification of effective empty parking spaces and their boundaries is realized. The experimental results show that compared with the recognition of traditional parking lines and parking angles, this method can identify effective empty parking spaces even when the light conditions are complex and the parking spaces are partially occupied by adjacent vehicles, which simplifies the recognition algorithm and improves the reliability of the parking spaces identification.

scholarly journals A fast template matching algorithm based on principal orientation difference

2018 ◽  
Vol 15 (3) ◽  
pp. 172988141877822 ◽  
Author(s):  
Jichao Jiao ◽  
Xin Wang ◽  
Zhongliang Deng ◽  
Jichang Cao ◽  
Weihua Tang
Keyword(s):  
Real Time ◽  
Template Matching ◽  
Feature Points ◽  
Matching Method ◽  
Matching Algorithm ◽  
Training Samples ◽  
Illumination Changes ◽  
Orientation Difference ◽  
Direction Information ◽  
State Of Art

In the case that the background scene is dense map regularization complex and the detected objects are low texture, the method of matching according to the feature points is not applicable. Usually, the template matching method is used. When training samples are insufficient, the template matching method gets a worse detection result. In order to resolve the problem stably in real time, we propose a fast template matching algorithm based on the principal orientation difference feature. The algorithm firstly obtains the edge direction information by comparing the images that are binary. Then, the template area is divided where the different features are extracted. Finally, the matching positions are searched around the template. Experiments on the videos whose speed is 30 frames/s show that our algorithm detects the low-texture objects in real time with a matching rate of 95%. Compared with other state-of-art methods, our proposed method reduces the training samples significantly and is more robust to the illumination changes.

Detection and Tracking of Vehicle Target Based on Super-Resolution Reconstruction and Variable Template Matching

2014 ◽  
Vol 541-542 ◽  
pp. 1429-1432
Author(s):  
Jun Yong Ma ◽  
Shao Dong Chen ◽  
Sheng Wei Zhang
Keyword(s):  
Template Matching ◽  
Super Resolution ◽  
Image Sequence ◽  
Low Resolution ◽  
Matching Method ◽  
Matching Accuracy ◽  
High Quality ◽  
Resolution Image ◽  
Detection And Tracking ◽  
Image Super Resolution

Vehicle Target Detection and Tracking Method Based on Image Super-Resolution Reconstruction and Variable Template Matching is Put Forward. Firstly, a Nonlinear Iterative Algorithm is Applied to Reconstruct a Super-Resolution Image from Low Resolution Image Sequence; then, the Image is Standardized and the Movement Areas are Determined; Finally, the Variable Template Matching Method is Used to Detect and Track the Vehicle Targets in Movement Areas. from the Characteristics of Algorithm and the Experiment Results, we can see that the Proposed Algorithm Improves the Matching Accuracy of Target Tracking and Better Solves the Limitation of Missed Detection for Traditional Methods. the Reason of the Good Performance of the Proposed Algorithm Relies in High Quality Images Acquired by Super-Resolution Reconstruction from Low Resolution Image Sequence and the Application of Variable Template Matching Method.

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.

Extracting of Five Characteristic Parameters Using in Static Gesture Recognition

2013 ◽  
Vol 380-384 ◽  
pp. 3738-3741
Author(s):  
Hong Duan ◽  
Yang Luo
Keyword(s):  
Environmental Change ◽  
Gesture Recognition ◽  
Template Matching ◽  
Feature Vector ◽  
Characteristic Parameters ◽  
Recognition Method ◽  
Matching Method ◽  
Static Gesture Recognition ◽  
Length And Area ◽  
The Impact

Proposed a static gesture recognition method for identifying characteristics of the object in combination. With the feature vector composed of five features, such as the number of fingers, gesture outline convex defect characteristics, the length and area of contour and Hu matrix, we adopted the template-matching method to conduct the matching of featured parameters. Experiments show that the method successfully recognized static gestures under complex background and could reduce the impact of environmental change simultaneously.

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