Detection of Microbubbles Using the Hough Transform

2013 ◽  
Vol 378 ◽  
pp. 478-482
Author(s):  
Yoshihiro Mitani ◽  
Toshitaka Oki
Keyword(s):  
Image Processing ◽  
Error Rate ◽  
Hough Transform ◽  
Detection Method ◽  
Experimental Results ◽  
Average Error ◽  
Image Processing Techniques ◽  
Average Error Rate ◽  
Processing Techniques

The microbubble has been widely used and shown to be effective in various fields. Therefore, there is an importance of measuring accurately its size by image processing techniques. In this paper, we propose a detection method of microbubbles by the approach based on the Hough transform. Experimental results show only 4.49% of the average error rate of the undetected microbubbles and incorrectly detected ones. This low percentage of the error rate shows the effectiveness of the proposed method.

Image Processing Based on Three-Dimensional Stereo Vision

2014 ◽  
Vol 556-562 ◽  
pp. 5017-5020
Author(s):  
Ting Ting Wang
Keyword(s):  
Image Processing ◽  
Binocular Vision ◽  
Stereo Vision ◽  
Error Rate ◽  
Three Dimensional ◽  
Processing Method ◽  
Stereoscopic Vision ◽  
Average Error ◽  
Traditional Model ◽  
Average Error Rate

Three-dimensional stereo vision technology has the capability of overcoming drawbacks influencing by light, posture and occluder. A novel image processing method is proposed based on three-dimensional stereoscopic vision, which optimizes model on the basis of camera binocular vision and in improvement of adding constraints to traditional model, moreover ensures accuracy of later location and recognition. To verify validity of the proposed method, firstly marking experiments are conducted to achieve fruit location, with the result of average error rate of 0.65%; and then centroid feature experiments are achieved with error from 5.77mm to 68.15mm and reference error rate from 1.44% to 5.68%, average error rate of 3.76% while the distance changes from 300mm to 1200mm. All these data of experiments demonstrate that proposed method meets the requirements of three-dimensional imageprocessing.

scholarly journals Quantum-Assisted Retinal Drusen Detection Algorithm using Entropy-Based Image Processing Techniques

2020 ◽  
Vol 9 (3) ◽  
pp. 2251-2256
Keyword(s):  
Image Processing ◽  
Composite System ◽  
Detection Method ◽  
Research Work ◽  
Detection Algorithm ◽  
Image Processing Techniques ◽  
Sensitivity Specificity ◽  
Processing Techniques ◽  
Retinal Fundus ◽  
Retinal Drusen

Drusen identification is the fundamental operation in the automated diagnosis of eye diseases. Manual and automatic detection of the drusen in the retinal fundus images has been developed recently in the classical manner only. This work provides the quantum-based retinal drusen detection method using entropy-based image processing techniques. This algorithm is the composite system of two channels, classical and quantum channels for the preprocessing and drusen detection respectively. This research work has been evaluated with the databases of DRIVE, STARE, MESSIDOR, E-Optha-Ex and ONH-Hunter. This quantum-based approach will be analyzed with the results of the existing classical methods and proves its efficiency from the calculations of sensitivity, specificity, accuracy and execution time.

scholarly journals Detection and Contouring of BAU-Kul using Image Processing Techniques

2019 ◽  
Vol 23 (2) ◽  
pp. 15-25
Author(s):  
MM Rahman ◽  
MMH Oliver
Keyword(s):  
Image Processing ◽  
High Accuracy ◽  
Contour Detection ◽  
Average Error ◽  
Market Prices ◽  
Image Processing Techniques ◽  
Random Samples ◽  
Automated Grading ◽  
Processing Techniques ◽  
Locally Grown

Automated grading and sorting of fruits during harvesting period are needed for securing better market prices. In order to introduce such automation facilities in Bangladesh, edging and contouring information of the locally grown fruits is important. This study reports the first endeavor towards the use of image processing techniques for a popular jujube variety (BAU-Kul) in Bangladesh. Image processing techniques were used for segmentation, and contouring on the basis of color Thresholding, edge detection and contour detection in Python-OpenCV software. Six random samples of BAU-Kul fruit were used for the research. Perimeter lengths obtained from the image analysis of the six samples ranged from 17.9 cm to 20.20 cm with an average of 19.29 (±1.02) cm. The measured lengths on the other hand, varied from 16.2 cm to 19.1 cm with an average of 17.75 (±1.3) cm. Consequently, the average error in calculation was limited to only 7.98%. This indicates the fact that images captured through mobile devices can be used for detection and contouring of BAU-Kul samples with fairly high accuracy (92.02%). These information provides a foreground basis of automation for the grading and sorting systems of BAU-Kul fruits in Bangladesh. Ann. Bangladesh Agric. (2019) 23(2) : 15-25

Anomalies in the Hough Transform of Kikuchi Bands in EBSD

2001 ◽  
Vol 7 (S2) ◽  
pp. 364-365
Author(s):  
Xiaodong Tao ◽  
Alwyn Eades
Keyword(s):  
Image Processing ◽  
Hough Transform ◽  
Average Intensity ◽  
Linear Features ◽  
Image Processing Techniques ◽  
Processing Techniques ◽  
The Way

The Hough Transform is widely used to detect linear features in image processing techniques. However, the features sought in the EBSD patterns are typically Kikuchi bands from low-index crystal planes, which are not lines but are bands of above average intensity bordered by dark bands. This gives rise to a characteristic shaped peak in the Hough transform that has been called the “butterfly” shape. in most cases, to reduce noise, the Hough Transform is convoluted with a mask having a matching “butterfly” shape. Unfortunately, this method sacrifices resolution through averaging the intensity of neighboring pixels. We have been concerned to use the Hough transform to locate the position of the Kikuchi bands with the highest possible precision. in order to achieve this goal we have looked into the way the Hough transform works on Kikuchi bands in detail, and found some anomalies that must be considered if accuracy is to be achieved.

scholarly journals Penerapan Metode Sobel Edge Detection dan Image Processing Untuk Mengetahui Diameter Apel Fuji Menggunakan Aplikasi Matlab

2020 ◽  
Vol 7 (3) ◽  
pp. 450
Author(s):  
Alima Hakkon Hasibuan ◽  
Taronisokhi Zebua ◽  
Rivalri Kristianto Hondro
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Detection Method ◽  
Selling Price ◽  
Image Processing Techniques ◽  
Sobel Edge Detection ◽  
Yellow Line ◽  
Edge Detection Method ◽  
Processing Techniques

Fuji apples (Malus Domestika) are fruits that contain a lot of antioxidants. Besides the fruit flesh, the apple also contains pectin. Fuji apples are red and have a yellow line. The size of apples can affect the selling price of apples, the determination of the size of apples can be seen from the size of the diameter, measuring the diameter of apples is usually done visually by comparing apples. Based on these problems, a research is needed to develop a system to determine the diameter of fuji apples by using image processing techniques to find the diameter. This measurement process uses the matlab application and tests with the sobel edge detection method and image processing to see the more visible edges of the lines. The results showed that the developed system was able to obtain images and identify the diameter of fuji apples

scholarly journals Prediksi Harga Bahan Pokok Nasional Jangka Pendek Menggunakan ARIMA

2017 ◽  
Vol 3 (2) ◽  
pp. 107 ◽  
Author(s):  
Mohammad Arif Rasyidi
Keyword(s):  
Error Rate ◽  
Arima Model ◽  
Commodity Prices ◽  
Experimental Results ◽  
Average Error ◽  
Short Term ◽  
Price Fluctuation ◽  
Price Prediction ◽  
Average Error Rate ◽  
Preventive Actions

Abstrak— Fluktuasi harga bahan pokok yang tidak terkendali dapat menyebabkan kerugian bagi konsumen maupun produsen. Salah satu langkah untuk mengatasi permasalahan tersebut yaitu dengan membuat prediksi harga yang akurat sehingga tindakan preventif dapat dilakukan untuk meminimalkan gejolak harga. Dalam studi ini, ARIMA digunakan untuk memprediksi harga bahan pokok nasional dalam jangka pendek. Data harga harian dari dua belas bahan pokok pada empat horizon prediksi (1 hingga 30 hari ke depan) digunakan untuk menguji kinerja ARIMA dalam memprediksi harga bahan pokok. Hasil eksperimen menujukkan bahwa model ARIMA yang dihasilkan mampu memprediksi harga dengan tingkat error rata-rata sebesar 2.22%. Kata Kunci— ARIMA, Bahan Pokok, Prediksi, PeramalanAbstract— Uncontrolled price fluctuation of basic commodities can harm both consumers and producers. One way to overcome the problem is by making accurate price prediction so that preventive actions can be conducted to minimize the price fluctuation. In this study, ARIMA is used to make short-term price prediction of national basic commodities. Daily pricing data of twelve commodities in four prediction horizons (1 to 30 days ahead) is used to test the performance of ARIMA in predicting the commodity prices. The experimental results showed that the ARIMA model was able to predict the price quite accurately with an average error rate of 2.22%. Keywords— ARIMA, Basic Commodities, Forecast, Prediction

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