An industrial visual inspection system that uses inductive learning

Aksoy, Mehmet Sabih; Torkul, Orhan; Cedi̇moğlu, İsmail Hakkı

doi:10.1023/b:jims.0000034120.86709.8c

Cited by 26 publications

(18 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are numerous applications of template matching from the quality control in industrial application [24] to navigation system for mobile robots [25] or edge detection in image processing applications [26]. In our study we will use template matching to find the contour of a template for laser cutting application.…”

Section: Template Matchingmentioning

confidence: 99%

A novel rotation-invariant template matching based on HOG and AMDF for industrial laser cutting applications

Arslan

Demirci

Altun

et al. 2013

2013 9th International Symposium on Mechatronics and Its Applications (ISMA)

View full text Add to dashboard Cite

A new real-time rotation-invariant template matching is proposed for industrial laser cutting applications. The technique is based on Histogram of Oriented Gradients (HOG) algorithm to remove rotational angle before the template matching process. It exploits the HOG and the Average Magnitude Difference Function (AMDF) features for rotationinvariance. Since HOG features are robust against illumination effects, the proposed algorithm is suitable for harsh industrial environments. The final aim of this study is to devise a method to detect the contour of an object, which will automatically be cut from a sheet of material.

show abstract

Section: Template Matchingmentioning

confidence: 99%

A novel rotation-invariant template matching based on HOG and AMDF for industrial laser cutting applications

Arslan

Demirci

Altun

et al. 2013

2013 9th International Symposium on Mechatronics and Its Applications (ISMA)

View full text Add to dashboard Cite

show abstract

“…This method can be used in manufacturing as part of the quality control (Aksoy, Torkul, & Cedimoglu, 2004), navigating the mobile robot (Kyriacou, Bugmann, & Lauria, 2005), or as detecting the vehicle types in main road (Thiang, 2001). Used 4 template matching techniques, namely:…”

Section: Introductionmentioning

confidence: 99%

Implementation of Template Matching Method for Door Lock Security System Using Raspberry Pi

Widiawan¹,

Kautsar²,

Purnomo³

et al. 2017

VOLT : Scientific Journal of Electrical Engineering Education

View full text Add to dashboard Cite

In several location, security system is becoming priority. One of the location is laboratory. There are many valuable research tools and equipment in the laboratory, so to improve the security system. Generally, the access to entry the laboratory is equipped with digital safety system. Computer Control System Laboratory at Information Technology Department of Jember State Polytechnic uses RFID-Card as access right for entrance to the laboratory. RFID-Card also function as ID-Card (printed with photo and biodata), and packaged to fit in user clothes pocket. However, using RFID gives less of flexibility. The user must remove the ID-Card and attach the card in the RFID reader box. Therefore, in this study will designed a door lock security system based on the image processing to replace the use of RFID. Later, user simply position themselves in the Pi Camera work area. Processed data from camera, the matched with image data which stored in the database. The database contains photo of laboratory members which listed on the employee IDCard. Template matching method is used as image matching method which stored in Raspberry Pi database. If the image which captured by camera is matched with the image data in the database, the controller will give entry access to the user. Based on the experimental results, template matching method has a success rate of 96%.

show abstract

“…One of the simple methods is called full search algorithm, an algorithm that scans the entire image at each pixel and assesses the similarity or dissimilarity between a pattern and the local 2D windows for all pixel locations. Obviously, the high complexity and time-consuming computation of the full search algorithm are not conducive for its large-scale applications to manufacturing quality control [1], texture synthesis [2], motion estimation [3], [4], object detection [5], [6], road tracking, behavior recognition [7] and image denoising [8] etc.…”

Section: Introductionmentioning

confidence: 99%

Fast Orthogonal Haar Transform PatternMatching via Image Square Sum

Cai

2014

IEEE Trans. Pattern Anal. Mach. Intell.

View full text Add to dashboard Cite

Although using image strip sum, an orthogonal Haar transform (OHT) pattern matching algorithm may have good performance, it requires three subtractions to calculate each Haar projection value on the sliding windows. By establishing a solid mathematical foundation for OHT, this paper based on the concept of image square sum, proposes a novel fast orthogonal Haar transform (FOHT) pattern matching algorithm, from which a Haar projection value can be obtained by only one subtraction. Thus, higher speed-ups can be achieved, while producing the same results with the full search pattern matching. A large number of experiments show that the speed-ups of FOHT are very competitive with OHT in most cases of matching one single pattern, and generally higher than OHT in all cases of matching multiple patterns, exceeding other high-level full search equivalent algorithms.

show abstract

An industrial visual inspection system that uses inductive learning

Cited by 26 publications

References 4 publications

A novel rotation-invariant template matching based on HOG and AMDF for industrial laser cutting applications

A novel rotation-invariant template matching based on HOG and AMDF for industrial laser cutting applications

Implementation of Template Matching Method for Door Lock Security System Using Raspberry Pi

Fast Orthogonal Haar Transform PatternMatching via Image Square Sum

Contact Info

Product

Resources

About