Segmentation of Cotton Leaves Blade Based on Global Threshold and Morphological Operation

2019 ◽  
pp. 307-313
Author(s):  
Janwale Asaram Pandurang ◽  
S. Lomte Santosh ◽  
Kale Suhash Babasaheb
Keyword(s):  
Morphological Operation ◽  
Global Threshold

Segmentation in Food Images

2006 ◽  
pp. 340-354
Author(s):  
Domingo Mery ◽  
Franco Pedreschi
Keyword(s):  
Roc Curve ◽  
Binary Image ◽  
High Contrast ◽  
Morphological Operation ◽  
Robust Algorithm ◽  
Optimal Linear Combination ◽  
Global Threshold ◽  
Receiver Operation Characteristic ◽  
Optimal Linear ◽  
Food Image

In this chapter, a robust algorithm for segmenting food imagery from a background is presented using colour images. The proposed method has three steps: (i) computation of a high contrast grey value image from an optimal linear combination of the RGB colour components; (ii) estimation of a global threshold using a statistical approach; and (iii) a morphological operation in order to fill the possible holes presented in the segmented binary image. Although the suggested threshold separates the food image from the background very well, the user can modify it in order to achieve better results. The algorithm was implemented in Matlab and tested on 45 images taken under very different conditions. The segmentation performance was assessed by computing the area Az under the Receiver Operation Characteristic (ROC) curve. The achieved performance was Az = 0.9982.

IMPLEMENTASI METODE OPERASI MORFOLOGIS DALAM PERBAIKAN HASIL SEGMENTASI CITRA DIGITAL GORGA BATAK

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Ojahan Sihombing ◽  
Efori Buulolo ◽  
Henry Kristian Siburian
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Operation Technique ◽  
Regional Culture ◽  
Human Beings ◽  
Morphological Operation ◽  
Research Technology ◽  
Operation Method ◽  
Image Improvement

As the development of research technology on Digital Image Processing continues to grow. Likewise, the improvement of the quality of sharpness / subtlety of the Gorga Batak images is an important thing to improve. This is one of the ways to preserve the Batak tribe area so that Gorga-gorga are still remembered and more interpreted. The cause of the need to be improved is the image of Gorga Batak is caused by several factors that cause the image to be less beautiful if it is interpreted by human beings such as the shape has been blurred (dark) due to shooting / shooting, has noise black spots on the image (noise), and the color is dull out of date. As an effort to improve image, the segmentation process is carried out by doing edge detection on the image, then the Morphological Operation Method will be implemented as one of the methods in Digital Image Processing that implements image quality improvement based on the shape and structure of the image. In this image processing, the Dilation Operation Technique and Operation Technique will be carried out. In Operation Dilation Techniques works by adding several segments (pixels) in the image so as to increase the integrity / sharpness of the structure of the image. While the Erosion Operation Technique will reduce / refine unnecessary parts / segments of the image so that the resulting image looks smoother, so that it can be more interpreted by humans and can be reused both as documentation of regional culture and so on. Using this method is expected to be able to improve and improve the quality / sharpness of Citra Gorga Batak. To facilitate the operation of the program design tools will be used, namely Matlab.Keywords: Image Improvement, Gorga Batak, Morphological Operation Method

scholarly journals Quantitative investigation of memory recall performance of a computational microcircuit model of the hippocampus

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Nikolaos Andreakos ◽  
Shigang Yue ◽  
Vassilis Cutsuridis
Keyword(s):  
Recall Performance ◽  
Network Size ◽  
Excitatory Input ◽  
Quantitative Investigation ◽  
Great Cost ◽  
Neuronal Populations ◽  
Global Threshold ◽  
Tightly Coupled ◽  
Memory Pattern ◽  
Determining Factor

AbstractMemory, the process of encoding, storing, and maintaining information over time to influence future actions, is very important in our lives. Losing it, it comes with a great cost. Deciphering the biophysical mechanisms leading to recall improvement should thus be of outmost importance. In this study, we embarked on the quest to improve computationally the recall performance of a bio-inspired microcircuit model of the mammalian hippocampus, a brain region responsible for the storage and recall of short-term declarative memories. The model consisted of excitatory and inhibitory cells. The cell properties followed closely what is currently known from the experimental neurosciences. Cells’ firing was timed to a theta oscillation paced by two distinct neuronal populations exhibiting highly regular bursting activity, one tightly coupled to the trough and the other to the peak of theta. An excitatory input provided to excitatory cells context and timing information for retrieval of previously stored memory patterns. Inhibition to excitatory cells acted as a non-specific global threshold machine that removed spurious activity during recall. To systematically evaluate the model’s recall performance against stored patterns, pattern overlap, network size, and active cells per pattern, we selectively modulated feedforward and feedback excitatory and inhibitory pathways targeting specific excitatory and inhibitory cells. Of the different model variations (modulated pathways) tested, ‘model 1’ recall quality was excellent across all conditions. ‘Model 2’ recall was the worst. The number of ‘active cells’ representing a memory pattern was the determining factor in improving the model’s recall performance regardless of the number of stored patterns and overlap between them. As ‘active cells per pattern’ decreased, the model’s memory capacity increased, interference effects between stored patterns decreased, and recall quality improved.

scholarly journals Distributed and morphological operation-based data collection algorithm

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771771759 ◽  
Author(s):  
Yalin Nie ◽  
Haijun Wang ◽  
Yujie Qin ◽  
Zeyu Sun
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Network Lifetime ◽  
Algorithm Analysis ◽  
Wireless Sensor ◽  
Morphological Operation ◽  
Event Monitoring ◽  
Binary Images ◽  
Structuring Element

When monitoring the environment with wireless sensor networks, the data sensed by the nodes within event backbone regions can adequately represent the events. As a result, identifying event backbone regions is a key issue for wireless sensor networks. With this aim, we propose a distributed and morphological operation-based data collection algorithm. Inspired by the use of morphological erosion and dilation on binary images, the proposed distributed and morphological operation-based data collection algorithm calculates the structuring neighbors of each node based on the structuring element, and it produces an event-monitoring map of structuring neighbors with less cost and then determines whether to erode or not. The remaining nodes that are not eroded become the event backbone nodes and send their sensing data. Moreover, according to the event backbone regions, the sink can approximately recover the complete event regions by the dilation operation. The algorithm analysis and experimental results show that the proposed algorithm can lead to lower overhead, decrease the amount of transmitted data, prolong the network lifetime, and rapidly recover event regions.

scholarly journals Global threshold dynamics of an SVIR model with age-dependent infection and relapse

2016 ◽  
Vol 11 (sup2) ◽  
pp. 427-454 ◽  
Author(s):  
Jinliang Wang ◽  
Jiying Lang ◽  
Yuming Chen
Keyword(s):  
Threshold Dynamics ◽  
Global Threshold ◽  
Age Dependent

scholarly journals Ventricle Boundary in CT: Partial Volume Effect and Local Thresholds

2010 ◽  
Vol 2010 ◽  
pp. 1-6 ◽  
Author(s):  
Ihar Volkau ◽  
Fiftarina Puspitasari ◽  
Wieslaw L. Nowinski
Keyword(s):  
Computed Tomography ◽  
Cerebrospinal Fluid ◽  
Grey Matter ◽  
Ground Truth ◽  
Gaussian Mixture ◽  
Volume Effect ◽  
Partial Volume Effect ◽  
Partial Volume ◽  
Image Histogram ◽  
Global Threshold

We present a mathematical frame to carry out segmentation of cerebrospinal fluid (CSF) of ventricular region in computed tomography (CT) images in the presence of partial volume effect (PVE). First, the image histogram is fitted using the Gaussian mixture model (GMM). Analyzing the GMM, we find global threshold based on parameters of distributions for CSF, and for the combined white and grey matter (WGM). The parameters of distribution of PVE pixels on the boundary of ventricles are estimated by using a convolution operator. These parameters are used to calculate local thresholds for boundary pixels by the analysis of contribution of the neighbor pixels intensities into a PVE pixel. The method works even in the case of an almost unimodal histogram; it can be useful to analyze the parameters of PVE in the ground truth provided by the expert.

scholarly journals Identifikasi Kematangan Cabai Menggunakan Operasi Morfologi (Opening dan Closing) dan Metode Backpropagation

SISTEMASI ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 96
Author(s):  
Khairullah Khairullah ◽  
Erwin Dwika Putra
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Confusion Matrix ◽  
Training Data ◽  
Morphological Operations ◽  
Morphological Operation ◽  
Backpropagation Method ◽  
Grouping Method ◽  
Opening And Closing

AbstrakIdentifikasi kualitas buah cabai biasanya masih menggunakan cara visual secara langsung atau sortir secara manual oleh petani, dengan menggunakan sistem ini sering kali terjadi beberapa kesalahan setiap melakukan sortir yang disebabkan oleh petani yang melakukan sortir merasa terlalu lelah. Dengan menggunakan komputasi pengolahan citra digital, untuk melakukan identifikasi pengelompokan buah cabai yang matang dan mentah dapat membantu para petani, Teknik pengelompokan ini akan menggunakan metode pengelompokan berdasarkan warna. Metode pengelompokan tersebut sebelumnya akan dilakukan operasi morfologi pada citra yang telah diambil. Pendekatan operasi morfologi pada penelitian ini adalah Opening and Closing, pada operasi morfologi akan menghilangkan noise dan menebalkan objek dari inputan gambar. Metode Bacpropagatioan akan mengolah data latih sebanyak 10 data latih mendapatkan 6 iterasi perhitungan dan setelah diuji menggunakan data uji hasil yang didapatkan yaitu tingkat pengenalan rata-rat mendapatkan perhitungan sebanyak 7 iterasi metode Bacpropagation. Hasil dari penelitian ini juga dihitung menggunakan Confusion Matrix dimana nilai Precision 90%, Recall 74%, dan Accuracy 70%, maka dapat disimpulkan bahwa Operasi Morfologi dan Metode Backpropagation dapat digunakan untuk mengidentifikasi objek cabai.Kata Kunci: backpropagation, morfologi, identifikasi, opening and closing  AbstractIdentification of the quality of chili fruit is usually still using a visual way directly or sorting manually by farmers, using this system often occurs several errors, every sorting caused by farmers who do the sorting feel too tired. By using digital image processing computing, to identify the grouping of ripe and raw chili fruits can help farmers, this grouping technique will use a method of grouping based on color. The grouping method will previously perform morphological surgery on the image that has been taken. The morphological operation approach in this study is Opening and Closing, in morphological operations will eliminate noise and thicken objects from image input. Bacpropagatioan method will process training data as much as 10 training data get 6 iterations of calculations and after being tested using the test data obtained results that is the level of introduction of the average rat get a calculation of 7 iterations bacpropagation method. The results of this study were also calculated using Confusion Matrix where precision values of 90%, Recall 74%, and Accuracy 70%, it can be concluded that Morphological Operations and Backpropagation Method can be used to identify chili objects.Keywords: backpropagation, morfologi, identification, opening and closing

scholarly journals HOW TO OBTAIN A GLOBAL REFERENCE THRESHOLD IN AHP/ANP

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Claudio Garuti
Keyword(s):  
Real Life ◽  
Absolute Measurement ◽  
Threshold Value ◽  
Rate Of Change ◽  
Current Status ◽  
Medical Diagnoses ◽  
Specific Objective ◽  
Global Threshold ◽  
Disaster Assessment ◽  
The Difference

This paper has two main objectives. The first objective is to provide a mathematically grounded technique to construct local and global thresholds using the well-known rate of change method. The next objective, which is secondary, is to show the relevance and possibilities of applying the AHP/ANP in absolute measurement (AM) compared to the relative measurement (RM) mode, which is currently widely used in the AHP/ANP community. The ability to construct a global threshold would help increase the use of AHP/ANP in the AM mode (rating mode) in the AHP/ANP community. Therefore, if the first specific objective is achieved, it would facilitate reaching the second, more general objective.   For this purpose, a real-life example based on the construction of a multi-criteria index and threshold will be described. The index measures the degree of lag of a neighborhood through the Urban and Social Deterioration Index (USDI) based on an AHP risks model. The global threshold represents the tolerable lag value for the specific neighborhood. The difference or gap between the neighborhood’s current status (actual USDI value) and this threshold represents the level of neighborhood deterioration that must be addressed to close the gap from a social and urban standpoint. The global threshold value is a composition of 45 terminal criteria with their own local threshold that must be evaluated for the specific neighborhood. This example is the most recent in a large list of AHP applications in AM mode in vastly different decision making fields, such as risk disaster assessment, environmental assessment, the problem of medical diagnoses, social responsibility problems, BOCR analysis for the evolution of nuclear energy in Chile in the next 20 years and many others. (See list of projects in Appendix).

scholarly journals Decentralized detection of global threshold crossings using aggregation trees

2008 ◽  
Vol 52 (9) ◽  
pp. 1745-1761 ◽  
Author(s):  
Fetahi Wuhib ◽  
Mads Dam ◽  
Rolf Stadler
Keyword(s):  
Decentralized Detection ◽  
Global Threshold
Sign in / Sign up

Export Citation Format

Share Document