scholarly journals Fast Job Recognition and Sorting Based on Image Processing

2021 ◽  
Vol 38 (2) ◽  
pp. 421-429
Author(s):  
He Yujie
Keyword(s):  
Image Processing ◽  
Template Matching ◽  
Feature Fusion ◽  
Intelligent Manufacturing ◽  
Industrial Robots ◽  
Similarity Function ◽  
High Complexity ◽  
Moment Features ◽  
Susceptibility To Noise ◽  
Positioning Algorithm

With the advancement of artificial intelligence (AI) and the upgrading of intelligent manufacturers, the development of intelligent manufacturing is now propelled by the replacement of inefficient traditional assembly machines and operators with machine vision (MV)-based industrial robots. The classic job recognition and positioning algorithm has multiple shortcomings, such as high complexity, manual design of similarity function, and susceptibility to noise disturbance. To solve these shortcomings, this study presents a fast job recognition and sorting method based on image processing. Firstly, the extraction approach for wavelet moment features and wavelet descriptors was introduced, and the feature fusion based on echo state network (ESN) was detailed. Then, the authors explained the idea of job template matching, and described how to measure similarity and terminate the measurement during template matching. Experimental results fully manifest the effectiveness of our strategy for fast job recognition and sorting. Our method offers a new solution to rapid recognition and sorting of objects in other fields.

An Efficient Image-Based Method for Detection of Fastener on Railway

2011 ◽  
Vol 346 ◽  
pp. 731-737 ◽  
Author(s):  
Jin Feng Yang ◽  
Man Hua Liu ◽  
Hui Zhao ◽  
Wei Tao
Keyword(s):  
Image Processing ◽  
Efficient Method ◽  
Template Matching ◽  
Detection Method ◽  
Experimental Results ◽  
Feature Descriptor ◽  
Complex Environment ◽  
Computation Efficiency ◽  
The Status ◽  
Direction Field

This paper presents an efficient method to detect the fastener based on the technologies of image processing and optical detection. As feature descriptor, the Direction Field of fastener image is computed for template matching. This fastener detection method can be used to determine the status of fastener on the corresponding track, i.e., whether the fastener is on the track or missing. Experimental results are presented to show that the proposed method is computation efficiency and is robust for fastener detection in complex environment.

scholarly journals Fashion Product Classification through Deep Learning and Computer Vision

2019 ◽  
Vol 9 (7) ◽  
pp. 1385 ◽  
Author(s):  
Luca Donati ◽  
Eleonora Iotti ◽  
Giulio Mordonini ◽  
Andrea Prati
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Feature Extraction ◽  
Deep Learning ◽  
Template Matching ◽  
Learning Approaches ◽  
Visual Classification ◽  
Product Classification ◽  
Processing Techniques

Visual classification of commercial products is a branch of the wider fields of object detection and feature extraction in computer vision, and, in particular, it is an important step in the creative workflow in fashion industries. Automatically classifying garment features makes both designers and data experts aware of their overall production, which is fundamental in order to organize marketing campaigns, avoid duplicates, categorize apparel products for e-commerce purposes, and so on. There are many different techniques for visual classification, ranging from standard image processing to machine learning approaches: this work, made by using and testing the aforementioned approaches in collaboration with Adidas AG™, describes a real-world study aimed at automatically recognizing and classifying logos, stripes, colors, and other features of clothing, solely from final rendering images of their products. Specifically, both deep learning and image processing techniques, such as template matching, were used. The result is a novel system for image recognition and feature extraction that has a high classification accuracy and which is reliable and robust enough to be used by a company like Adidas. This paper shows the main problems and proposed solutions in the development of this system, and the experimental results on the Adidas AG™ dataset.

scholarly journals Fusion Mode and Style Based on Artificial Intelligence and Clothing Design

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Jiali Qiu ◽  
Lianghua Ma
Keyword(s):  
Artificial Intelligence ◽  
Three Dimensional ◽  
Intelligent Manufacturing ◽  
Industrial Robots ◽  
Design System ◽  
Design Elements ◽  
Advantages And Disadvantages ◽  
Clothing Design ◽  
The Right ◽  
Intelligent Clothing

With the upgrading of intelligent manufacturing, industrial robots will play an important role in the garment industry. The purpose of this article was to study the pattern and style based on the integration of artificial intelligence and clothing design. In this article, the digital modeling of clothing design and the case analysis of intelligent clothing design are described using the method of comparative experiment. The experimental results are obtained from the analysis of fuzzy number of clothing design language evaluation, three-dimensional human body construction clothing size, clothing design elements and auxiliary functions, and the analysis of the advantages and disadvantages of clothing design system. The popular clothing sample is D4 (0.4862), which is 20% higher than other products. It can be concluded that the model proposed in this article can grasp the needs of consumers and select the right one according to the market positioning. The fabric mass production fashion brand can significantly improve the efficiency and satisfaction of the fabric selection decision-making process. It provides enough technical support and style model for intelligent clothing design.

scholarly journals Discussion on Teaching Method of Digital Image Processing Technology Based on PBL

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Lifang Chen
Keyword(s):  
Image Processing ◽  
Digital Media ◽  
Digital Image Processing ◽  
Digital Image ◽  
Teaching Method ◽  
Teaching Style ◽  
Intelligent Manufacturing ◽  
Processing Technology ◽  
Media Technology ◽  
Image Processing Technology

A required course for students majoring in digital media technology, computer science and technology, or artificial intelligence is “digital image processing technology.” Aviation, medical image processing, intelligent manufacturing, and many more fields may benefit from the knowledge and skills gained in this course. It contains the qualities of “many conceptions, numerous principles, and various formulae,” according to the curriculum. As a result, traditional teaching techniques only pay attention to the explanation of theoretical information, which may easily lead students to create uninteresting feelings; they have abandoned the in-depth investigation and learning of the course material. The PBL approach is used to provide an interest-driven and problem-solving-driven grounded teaching technique that naturally connects the theoretical foundation with real-world examples and problems. We utilize case teaching to assist students better comprehend theoretical information and to teach them how to apply theoretical knowledge to actual difficulties they encounter in their lives. During the course of many semesters of practice, we discovered that our teaching approaches are quite popular with students. The deployment of a teaching style focused on problem-based learning has resulted in significant improvements in students’ learning initiative, practical ability, and innovative ability.

scholarly journals Template Matching dalam Otomatisasi Penghitung Sel Keping Darah Berbasis Image Processing untuk Deteksi Dini Derajat Penyakit Demam Berdarah

2018 ◽  
Vol 14 (1) ◽  
pp. 1
Author(s):  
Amelia Yolanda ◽  
Deddy Prayama ◽  
Aulia Ramadhani
Keyword(s):  
Image Processing ◽  
Dengue Hemorrhagic Fever ◽  
Template Matching ◽  
Hemorrhagic Fever ◽  
Matching Method ◽  
System Testing ◽  
Blood Tests ◽  
Automatic Systems

One of the diseases that can be detected through blood tests is Dengue Hemorrhagic Fever (DHF). The number of platelets are one of the guidelines used by doctors diagnosing DHF. Actually, platelets can be calculated manually, but it will be very difficult if the platelets are counted quite a lot. So, we need a technology that can calculate the number of platelets quickly and automatized to get more accurate results.   The automatic systems built by using the template matching method with  image processing include HSL Segmentation with Luminance type and Reverse Color Manipulation. After building the system, the system will automatically look for objects that match the template in the sample image and then give the marking and calculate it.The overall system testing results are the number of platelets which are then classified manually at what degree of DHF.

scholarly journals Real-Time Video Road Sign Detection and Tracking using Image Processing and Autonomous Car

2019 ◽  
Vol 8 (12S2) ◽  
pp. 495-500
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Template Matching ◽  
High Rate ◽  
Image Processing Technique ◽  
Video Frame ◽  
Road Signs ◽  
Detection And Tracking ◽  
Road Sign ◽  
Sign Detection

Detection and monitoring of real-time road signs are becoming today's study in the autonomous car industry. The number of car users in Malaysia risen every year as well as the rate of car crashes. Different types, shapes, and colour of road signs lead the driver to neglect them, and this attitude contributing to a high rate of accidents. The purpose of this paper is to implement image processing using the real-time video Road Sign Detection and Tracking (RSDT) with an autonomous car. The detection of road signs is carried out by using Video and Image Processing technique control in Python by applying deep learning process to detect an object in a video’s motion. The extracted features from the video frame will continue to template matching on recognition processes which are based on the database. The experiment for the fixed distance shows an accuracy of 99.9943% while the experiment with the various distance showed the inversely proportional relation between distances and accuracies. This system was also able to detect and recognize five types of road signs using a convolutional neural network. Lastly, the experimental results proved the system capability to detect and recognize the road sign accurately.

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