scholarly journals SMT Component Inspection in PCBA’s using Image Processing Techniques

In the present evolving technology, an Automated Optical Inspection is a solution for identifying the various types of defects occurring in assembled PCB with SMT components. As these high-end machines are expensive, moreover the small scale industries can’t afford such a huge investment, in this paper a low cost image processing technique where a good known reference image is compared with the acquired image is being tried. This work provides an automated approach for identifying few of the defects related to the SMT components found in the assembled PCB, using three different techniques namely Contour Analysis, Optical Character Recognition and Pixel Subtraction for identifying shifted components, value of the components and missing components respectively in LabVIEW platform. The time taken for identifying the various defects through different techniques are calculated and tabulated. Using these techniques the number of errors can be decreased in turn the end performance can also be enhanced with the increased production yield.

Author(s):  
Kirad Varad Vinay ◽  
Indla Omkar Balaobaiah ◽  
Mujawar Sohail Mahiboob ◽  
Shinde Dinesh Nagnath ◽  
Prof. Darshana Patil

According to survey taken the total number of vehicles in [1] India were 260 million. Therefore, there is a need to develop Automatic Number Plate Recognition (ANPR) systems [1] in India because of the large number of vehicles travelling on the roads. [1] It would also help in proper tracking of the vehicles, traffic examining, finding stolen vehicles, supervising parking toll and imposing strict actions against red light breaching. Automatic number plate recognition is image processing technique for finding number plate from image and extracting characters from detected number plate. ANPR in India has always been challenging due to different lighting conditions, changes in fonts, shapes, angles, letters size, number of lines and padding between lines, different languages used. In our project we proposed a model that can detects number plate with considering all irregularities. this system uses Computer vision and machine learning technology in order to detect number plate from image. In our proposed system number plate can be of different fonts and non-roman script. For identification of characters from number plate we use OCR (Optical character recognition) technique. OCR involves two parts: Character segmentation and Character Recognition. This OCR system can be used to extract characters of different fonts and non-roman script. The Quality of OCR depends on the quality of image, image contrast, text font style and size. To improve quality of OCR we can use image processing technique to enhance quality of image.


2021 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Bafreen Najeb Mohammed ◽  
Hawar B. Ahmad

The open-source hardware development platform Arduino has been growing in recent years. Nowadays, the Arduino platform became one of the important parts in remote control and monitor of electrical devices. This paper aims to propose an application of digital image processing along with Arduino, which can be useful in car-parking place to be more secure. Arduino will detect the car and take a picture for its plat and send it to the system. Then, system applies digital image processing technique in the image. Different algorithms are incorporated in system such as segmentation, normalization, localization, orientation and optical character recognition (OCR) which analyze certain features in image and predicts car plate numbers. Afterwards the resulting data are compared against records in a stored database.


2021 ◽  
Vol 11 (4) ◽  
pp. 7291-7295
Author(s):  
M. U. Farooq ◽  
A. Ahmed ◽  
S. M. Khan ◽  
M. B. Nawaz

Increased traffic flow results in high road occupancy. Traffic road occupancy is often used as a parameter for the prediction of traffic conditions by traffic engineers. Although traffic monitoring systems are based on a large number of technologies, challenges are still present. Most of the methods work efficiently for free-flow traffic but not in heavy congestion. Image processing techniques are more effective than other methods, as they are based on loop sensors and detectors to monitor road traffic. A huge number of image frames are processed in image processing hence there is a need for a more efficient and low-cost image processing technique for accurate vehicle detection. In this paper, a novel approach is adopted to calculate road occupancy. The proposed framework has robust performance under road conjunction and diverse environmental conditions. A combination of image segmentation threshold technique and shadow removal technique is used. The study comprised of segmenting 1056 images extracted from recorded videos. The obtained results by image segmentation were compared with traffic road occupancy calculated manually using Autocad. A final percentage difference of 8.7 was observed.


2020 ◽  
Vol 9 (1) ◽  
pp. 58
Author(s):  
Beatriz M. Dias ◽  
Victor F. Velázquez ◽  
Rodrigo F. Lucena ◽  
José M. Azevedo Sobrinho

The technique of description and characterization of rocks with the aid of a polarized light microscope is a well-established practice in the fields of mineralogy and petrology. However, because geological materials are inherently highly variable on a small scale, capturing good-quality images, particularly of the fine details present in the mineral grains that compose the rock, is the main difficulty encountered when a thin section is examined under a petrographic microscope. Combining petrographic concepts and digital image processing methods, the principal aim of this paper is to provide a practical approach to digital image treatment with specific software, and its immediate application in the micromorphological characterization of minerals. In addition to the basic calibration of color, brightness, and contrast, three different methods of digital image processing in the spatial domain, following the principles of embossed surface, negative image, and edge detection techniques, were applied to the images. The use of these primary filters was found to be efficient for detailed characterization of the mineralogical phases involved in the different types of microstructures. However, special care must be taken regarding the sensitivity and accuracy parameters to avoid the exclusion of information or the addition of noise to the image. Although research has focused on the distinction of several types of textural features in rock-forming minerals, these techniques can be employed in other areas of investigation, in both academic and industrial settings, to diagnose textures of microtectonic deformation, soil micromorphological features, the proportions of the original ingredients in concretes, and the mineralogical modal determination of ceramics of archeological origin and to characterize mineral raw materials for the manufacture of technological products.


Author(s):  
Yasushi Kokubo ◽  
Hirotami Koike ◽  
Teruo Someya

One of the advantages of scanning electron microscopy is the capability for processing the image contrast, i.e., the image processing technique. Crewe et al were the first to apply this technique to a field emission scanning microscope and show images of individual atoms. They obtained a contrast which depended exclusively on the atomic numbers of specimen elements (Zcontrast), by displaying the images treated with the intensity ratio of elastically scattered to inelastically scattered electrons. The elastic scattering electrons were extracted by a solid detector and inelastic scattering electrons by an energy analyzer. We noted, however, that there is a possibility of the same contrast being obtained only by using an annular-type solid detector consisting of multiple concentric detector elements.


Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.


Author(s):  
Yashpal Jitarwal ◽  
Tabrej Ahamad Khan ◽  
Pawan Mangal

In earlier times fruits were sorted manually and it was very time consuming and laborious task. Human sorted the fruits of the basis of shape, size and color. Time taken by human to sort the fruits is very large therefore to reduce the time and to increase the accuracy, an automatic classification of fruits comes into existence.To improve this human inspection and reduce time required for fruit sorting an advance technique is developed that accepts information about fruits from their images, and is called as Image Processing Technique.


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