scholarly journals Identifying Arabica Raw Coffee Bean Varieties through Feature Extraction GLCM and Circularity

2018 ◽  
Vol 7 (4.44) ◽  
pp. 117
Author(s):  
M. Agung Nugroho ◽  
Maria Mediatrix Sebatubun ◽  
Sumiyatun .
Keyword(s):  
Image Processing ◽  
Processing Method ◽  
Image Feature ◽  
Coffee Bean ◽  
Gray Level ◽  
Tree Leaves ◽  
Image Processing Method ◽  
Coffee Farmers ◽  
Texture Size

The morphology of raw coffee bean which has colour, texture, size and circularity features are used as standardization to calculate the price and the quality of the raw coffee bean. Meanwhile, coffee farmers have difficulties to distinguish the coffee varieties based on the features of raw coffee bean. Generally, the way of the distinguish the varieties of the coffee is through their own visual perception in form of the tree, leaves, and raw coffee bean. They find it difficult to distinguish the coffee varieties due to the similarity of the varieties forms and colours. This research proposes to solve the problem through the image processing method as the second opinion to help the coffee farmers in identifying the coffee varieties. The research is conducted in three steps processes: The first is pre-processing by cropping the image of raw coffee bean. The second is extracting the image feature of raw coffee bean with Gray Level Co-occurrence Matrices (GLCM) and circularity feature. The last is classifying the feature with multilayer perceptron. The results of the image processing method indicate that the accuracy is 90% with sensitivity is 90%, and 90% specific. 

scholarly journals Study of filming condition for deep learning based crack detection method

2021 ◽  
Author(s):  
Tomotaka Fukuoka ◽  
Takahiro Minami ◽  
Makoto Fujiu ◽  
Junichi Takayama
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Service Life ◽  
Visual Inspection ◽  
Crack Detection ◽  
Detection Method ◽  
Processing Method ◽  
Inspection Method ◽  
Image Processing Method

Recently, the study of extending the service life of bridges has gained attention. In Japan, there are about 730,000 bridges with a length of 2 m or longer, and many of these were built during a period of high economic growth, and have now reached the end of their service life. Therefore, their rebuilding and the extension of their service life must be considered. However, some local public organizations have problems that insufficient manpower relative to the number of bridges to manage, as well as insufficient funding for maintenance. Thus, these organizations are unable to perform routine close visual inspections. Specific problems include “notably less staff and consulting technicians relative to the number of bridges to be managed” and “high inspection cost preventing from funding for repair.” As issues with the continuing close visual inspection of bridges are surfacing, the remote imaging system is expected to become a new inspection method that replaces close visual inspection. The practical potential of bridge inspections using images captured with a super-high-resolution camera was examined. A super-high-resolution camera enables us to take a wide area picture of a target bridge from a long distance. An image processing method could improve the efficiency of image-based inspection method. For example, a deep learning-based image processing method could extract a damaged area on a surface of a bridge automatically with high accuracy faster than human inspection. In general, the accuracy of an image processing method is affected by the quality of an input image. Filming conditions are one of the factors that determine the quality of a photo image. It is important to evaluate the effect of filming conditions to improve the reliability of an image processing method. In this paper, we evaluate the effect of the filming conditions for an image processing method by comparing the results of a deep learning-based crack detection method.

A Seam Image Processing Method Based on Wavelet Compress

2012 ◽  
Vol 472-475 ◽  
pp. 1353-1356
Author(s):  
Guo Hong Ma ◽  
Cong Wang ◽  
Ze Hong Yang
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Image Compression ◽  
Compression Ratio ◽  
Processing Method ◽  
Original Image ◽  
Image Processing Method

This paper designs several common methods, which is applied to situation that seam image could keep the same format when it is compressed, then analyses several problems existing in image processing. According a comparison in sundry compress methods’ characteristics and application, this paper eventually chooses a compress method that is suitable to original image, which is based on wavelet transform image compression and coding. Compress experiments shows that, the image compression ratio this paper designs could be exceeded up to 0.74 on the condition of the same format. The quality of seam image is basically intact, which could provide a desirable method in seam image efficient transmit.

Image Processing Based on Tuning-Parameter Stochastic Resonance

2008 ◽  
Author(s):  
Yong-gang Leng ◽  
Yan Guo ◽  
Ying Zhang
Keyword(s):  
Image Processing ◽  
Stochastic Resonance ◽  
Processing Method ◽  
Bistable System ◽  
Tuning Parameter ◽  
Tuning Parameters ◽  
System Parameters ◽  
Image Processing Method ◽  
Output Image

Bistable stochastic resonance (BSR) can change the image signal’s histogram distribution. In this paper, the influence of bistable system parameters on the contrast of the output image is investigated through the observation of histograms. An image-processing method of BSR via tuning parameters is proposed. The experiment on the treatment of an image plus noise has proved that it can improve the quality of the image effectively.

scholarly journals Research on Image Processing Method of High Voltage Switchgear Temperature Measurement

2020 ◽  
Vol 440 ◽  
pp. 032111
Author(s):  
Longji Du ◽  
Shi Zhang ◽  
Liming Chen ◽  
Jinglong Ye ◽  
Meiting Ma ◽  
...  
Keyword(s):  
Image Processing ◽  
Temperature Measurement ◽  
High Voltage ◽  
Processing Method ◽  
Image Processing Method

Defect Measurement in Welded Objects by Radiography Testing and Chambolle’s Image Processing Method

2021 ◽  
Vol 40 (2) ◽  
Author(s):  
Amir Movafeghi ◽  
Effat Yahaghi ◽  
Mahdi Mirzapour ◽  
Pouyan ShayganFar
Keyword(s):  
Image Processing ◽  
Processing Method ◽  
Image Processing Method
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