An 8-segmented 256×512 CMOS image sensor for processing element-coupled unified system in machine vision application

Machine vision studies opens a great opportunity for different domains as manufacturing, agriculture, aquaculture, medical research, also research studies and applications for better understanding of processes and operations. As scientists' efforts had been directed towards deep understanding of the particular material systems or particular classes of types of specific fruits, or diagnosis of patients through medical images classification and analysis, also real time detection and inspection of malfunction piece, or process, as various domains witnessed advancement through using machine vision techniques and methods.

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Influence of Sample Defocus and Large Thickness on Measurement Error in Machine Vision Application

Acta Optica Sinica ◽

10.3788/aos201535.0815002 ◽

2015 ◽

Vol 35 (8) ◽

pp. 0815002

Author(s):

来先家 Lai Xianjia ◽

徐文东 Xu Wendong ◽

赵成强 Zhao Chengqiang ◽

肖阳 Xiao Yang

Keyword(s):

Measurement Error ◽

Machine Vision ◽

Large Thickness ◽

Machine Vision Application ◽

Vision Application

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INSPECTION AND QUALITY CHECKING OF CERAMIC CUP USING MACHINE VISION TECHNIQUE: DESIGN AND ANALYSIS

Jurnal Teknologi ◽

10.11113/jt.v79.11280 ◽

2017 ◽

Vol 79 (5-2) ◽

Author(s):

Nursabillilah Mohd Ali ◽

Mohd Safirin Karis ◽

Siti Azura Ahmad Tarusan ◽

Gao-Jie Wong ◽

Mohd Shahrieel Mohd Aras ◽

...

Keyword(s):

Image Processing ◽

Computer Vision ◽

Machine Vision ◽

Image Sensor ◽

Histogram Method ◽

Inspection Method ◽

Inspection Process ◽

Set Up ◽

Vision Application ◽

Vision Technique

The development of inspection and quality checking using machine vision technique are discussed where the design of the algorithm mainly to detect the sign of defect when a sample product is used for inspection purposes. There are several constraints that a machine need to be improved based on technology used in vision application. CMOS image sensor as well as programming language and open source computer vision library were used in designing the inspection method. Experimental set-up was conducted to test the proposed technique for evaluate the effectiveness process. The experimental results were obtained and represented in graphical and image processing form. Besides, analysis and discussion were made according to obtained results. The proposed technique is able to perform the inspection process using good and defect ceramic cup based on detection technique. Moreover, based on the analysis gathered, the proposed technique able to differentiate between good and defect ceramic cup. The result shows that there is a difference frequency by 236 which is 2% of total value in pixels frequency. The frequency indicated as pixel frequency of image using histogram method based on scaled value of image.

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