scispace - formally typeset
Search or ask a question
Proceedings ArticleDOI

Automated object counting for visual inspection applications

01 Dec 2015-pp 801-806
TL;DR: An automatic counting method which requires only tolerance to be specified to calculate count of object is proposed which can be easily applied to different applications and shows high accuracy.
Abstract: Object counting is a popular operation in computer vision. It is also useful for visual inspection. When counting objects for visual inspection count of objects with similar features is calculated. In object counting feature extraction from input image is done and count is calculated by comparing these features values with cutoff values. These cutoff values are statically specified and used for particular application. In this paper an automatic counting method is proposed which requires only tolerance to be specified to calculate count of object. The proposed method calculates cutoff values at runtime and therefore it can be easily applied to different applications. The object count generated by proposed method is useful for visual inspection of input samples. The proposed method has basic four steps as Input image, Preprocessing, Segmentation and Counting. In fourth step ‘Counting’ cutoff values are calculated to generate final object count. Proposed automatic counting method is tested on two applications and it shows high accuracy.
Citations
More filters
Proceedings ArticleDOI
01 Sep 2017
TL;DR: A machine vision based non-contact defect detection algorithm for printed circuit boards (PCBs) has been developed, which detects and controls the holes on the PCB.
Abstract: Machine vision systems are used in industrial production areas to produce products with fast, perfect and high precision. These systems allow users to make highly accurate and non-contact measurements and can detect deficiencies in the production process. In this work, a machine vision based non-contact defect detection algorithm for printed circuit boards (PCBs) has been developed. In this approach, which detects and controls the holes on the PCB, first a reference image is taken from the system and feature extraction process is applied to this image. In this real-time working approach, the reference image is matched with the incoming test images and the missing holes on the PCB are precisely detected. Furthermore, it has been determined that the error amount is less than 2 μM in experimental studies. This approach, which works independently of color, position and direction, enables the defect detection process to be done very quickly and precisely.

35 citations


Additional excerpts

  • ...An example flowchart of literature [17] II....

    [...]

Posted Content
TL;DR: The proposed approach is based on Otsu thresholding and Hough transformation and performs automatic counting independently of product type and color and gives fast, accurate and reliable results.
Abstract: Machine vision applications are low cost and high precision measurement systems which are frequently used in production lines. With these systems that provide contactless control and measurement, production facilities are able to reach high production numbers without errors. Machine vision operations such as product counting, error control, dimension measurement can be performed through a camera. In this paper, a machine vision application is proposed, which can perform object-independent product counting. The proposed approach is based on Otsu thresholding and Hough transformation and performs automatic counting independently of product type and color. Basically one camera is used in the system. Through this camera, an image of the products passing through a conveyor is taken and various image processing algorithms are applied to these images. In this approach using images obtained from a real experimental setup, a real-time machine vision application was installed. As a result of the experimental studies performed, it has been determined that the proposed approach gives fast, accurate and reliable results.

23 citations


Cites background from "Automated object counting for visua..."

  • ...[13] performs the counting of the objects contained within the tablets....

    [...]

Journal ArticleDOI
31 Aug 2018-Sensors
TL;DR: The results showed that the ABBT is a useful tool for automating the assessment of unilateral gross manual dexterity, and provides additional information about the user’s performance.
Abstract: Objective assessment of motor function is an important component to evaluating the effectiveness of a rehabilitation process. Such assessments are carried out by clinicians using traditional tests and scales. The Box and Blocks Test (BBT) is one such scale, focusing on manual dexterity evaluation. The score is the maximum number of cubes that a person is able to displace during a time window. In a previous paper, an automated version of the Box and Blocks Test using a Microsoft Kinect sensor was presented, and referred to as the Automated Box and Blocks Test (ABBT). In this paper, the feasibility of ABBT as an automated tool for manual dexterity assessment is discussed. An algorithm, based on image segmentation in CIELab colour space and the Nearest Neighbour (NN) rule, was developed to improve the reliability of automatic cube counting. A pilot study was conducted to assess the hand motor function in people with Parkinson's disease (PD). Three functional assessments were carried out. The success rate in automatic cube counting was studied by comparing the manual (BBT) and the automatic (ABBT) methods. The additional information provided by the ABBT was analysed to discuss its clinical significance. The results show a high correlation between manual (BBT) and automatic (ABBT) scoring. The lowest average success rate in cube counting for ABBT was 92%. Additionally, the ABBT acquires extra information from the cubes' displacement, such as the average velocity and the time instants in which the cube was detected. The analysis of this information can be related to indicators of health status (coordination and dexterity). The results showed that the ABBT is a useful tool for automating the assessment of unilateral gross manual dexterity, and provides additional information about the user's performance.

10 citations


Cites methods from "Automated object counting for visua..."

  • ...The object counting can be done either by using a single feature or multiple features and then, by using cut-off values for those features, the final count is calculated [24]....

    [...]

Journal ArticleDOI
TL;DR: A HPC framework that provides new strategies for resource management and job scheduling, based on executing different applications in shared compute nodes, maximizing platform utilization is presented, which shows significant performance improvements up to 20% in the makespan and 10% in energy consumption compared to a non-optimized execution.
Abstract: This work presents a HPC framework that provides new strategies for resource management and job scheduling, based on executing different applications in shared compute nodes, maximizing platform utilization. The framework includes a scalable monitoring tool that is able to analyze the platform’s compute node utilization. We also introduce an extension of CLARISSE, a middleware for data-staging coordination and control on large-scale HPC platforms that uses the information provided by the monitor in combination with application-level analysis to detect performance degradation in the running applications. This degradation, caused by the fact that the applications share the compute nodes and may compete for their resources, is avoided by means of dynamic application migration. A description of the architecture, as well as a practical evaluation of the proposal, shows significant performance improvements up to 20% in the makespan and 10% in energy consumption compared to a non-optimized execution.

6 citations


Cites methods from "Automated object counting for visua..."

  • ...A distributed resource monitoring and prediction architecture was presented in [27] allowing the detection of the best set of machines to run an application based on the collected information and the result of a prediction algorithm, which evaluates the potential performance of a node....

    [...]

Journal ArticleDOI
TL;DR: In this article, an image processing technique for counting soybean seeds and separating damaged seeds was proposed, which can help save the time for counting the soybeans and separating the damaged seeds.
Abstract: This research proposed an image processing technique for counting soybean seeds and separating damaged seeds The technique used was to adjust the image to black and white so that the soybean seeds differ from the background color The second part, of the research, was the separation of soybean seeds using the distance transform method and the region growing method, to count soybean seeds In the third part, it focused on the separation of damaged seeds by the size, the circle shape and HSV of soybean seeds From 30 soybean seed images, the percentage of accuracy of counting and separating damaged seeds by naked eyes was 100 percent, and the average time spent was 1370 seconds The percentage of accuracy of counting the seeds by the developed program was 100 percent and the accuracy of the separation of damaged seeds was 9980 percent The average time spent was 649 seconds The experimental results showed that the developed program took 2 times less to count the soybean seeds than the naked eyes Therefore, the proposed algorithm of the program can help save the time for counting the soybean seeds and separate the damaged seeds

4 citations


Cites background from "Automated object counting for visua..."

  • ...It was defined that if the mean value of the object is the range of the mean of the object, it will be counted [3]....

    [...]

References
More filters
Proceedings ArticleDOI
11 Apr 2013
TL;DR: An efficient and cost effective computer vision system for automatic red blood cell counting using image based analysis is introduced.
Abstract: The major issue in clinical laboratory is to produce a precise result for every test especially in the area of Red Blood Cell (RBC) count. The number of red blood cell is very important to detect as well as to follow the treatment of many diseases like anaemia, leukaemia etc. Red blood cell count gives the vital information that help diagnosis many of the patient's sickness. The old conventional method of RBC counting under microscope gives an unreliable and inaccurate result depends on clinical laboratory technician skill. This method puts a lot of strain on the technician. Another method for RBC counting uses the automatic hematology analyzer, this machine is very costlier. So it is not possible all the hospital's clinical laboratory implement such an expensive machine to count the blood cell in their laboratory. This paper introduces an efficient and cost effective computer vision system for automatic red blood cell counting using image based analysis.

81 citations

Journal ArticleDOI
TL;DR: The paper describes some of the main tools and techniques used in this field of research, and then cites the references as sources for additional information and inspiration.
Abstract: A growing number of routine and research activities, in a wide variety of fields, have the counting of certain types of objects (cells, people, insects, etc.) as one of their main components. In most cases, such counting procedure is performed manually, in a process that is often lengthy and tedious. For that reason, several methods for automatically counting the objects of interest have been proposed in the last two decades. The vast majority of those methods rely on digital images containing the objects to provide an estimate as close as possible to the results manually obtained by human experts. The review is organized in a tutorial-like form, that is, instead of grouping the references according to a given criterion and then describing them, the paper describes some of the main tools and techniques used in this field of research, and then cites the references as sources for additional information and inspiration.

31 citations


"Automated object counting for visua..." refers methods in this paper

  • ...In automated object counting, count of objects is generated by capturing image and then applying step by step image processing operations[1]....

    [...]

  • ...Barbedo [1] presented a review of automatic object counting methods....

    [...]

Proceedings ArticleDOI
13 May 2013
TL;DR: Object counting in an image is one of the major challenges in image processing and marker controlled watershed segmentation along with thresholding technique gives satisfactory result.
Abstract: Object counting in an image is one of the major challenges in image processing. Image segmentation is used to segregate similar particles which help counting approximate total number of particles. Watershed segmentation technique is considered to be most efficient technique to solve problems of segregation contiguous objects. Thresholding technique is needed for counting objects in an image. Counting only with thresholding technique can give wrong impression. Using marker controlled watershed segmentation along with thresholding technique gives satisfactory result.

24 citations


"Automated object counting for visua..." refers methods in this paper

  • ...Md. Sharifur Rahman et al [7] presented a method for counting objects in image....

    [...]

  • ...Sharifur Rahman et al [7] presented a method for counting objects in image....

    [...]

Proceedings ArticleDOI
01 Sep 2014
TL;DR: A non-invasive method of counting fish in their natural habitat using automated analysis of video data and a heuristic blob tracking algorithm is presented.
Abstract: In this paper, we present a non-invasive method of counting fish in their natural habitat using automated analysis of video data. Our approach uses three modular components to preprocess, detect, and track the fish. The preprocessing reduces noise present in the image while enhancing the fish using several different techniques. The fish detection is based on two background subtraction algorithms which are computed independently and later combined with logical operations. The tracking is then carried out by a heuristic blob tracking algorithm. The paper presents a description of the proposed counting method as well as its experimental validation.

20 citations


"Automated object counting for visua..." refers methods in this paper

  • ...Ryan Fier et al [4] presented a fish counting method for under water video frames captured....

    [...]

Proceedings ArticleDOI
01 Feb 2014
TL;DR: In this paper, the development of automatic method for counting of silkworm eggs using image processing algorithm is presented. The algorithm is realized in LabVIEW graphical programming environment that shortens the development cycle.
Abstract: Sericulture activities involve rearing of pure races as parent seed crop and production of disease free silkworm seeds in grainages. Success of sericulture as a cash crop depends on production of disease free silkworm seeds supplied to farmers. Silkworm egg counting has to be done as farmers look to grainages for supply of silkworm seeds and pay accordingly. Conventional method of counting silkworm eggs relied on manual counting, which is time consuming and labor-intensive. Egg counting has to be done to generate statistics such as fecundity and hatching percentage. This paper presents the development of automatic method for counting of silkworm eggs using image processing algorithm. The algorithm is realized in LabVIEW graphical programming environment that shortens the development cycle. The algorithm realizes high precision and accuracy of counting.

12 citations