scholarly journals Segmentasi Citra Wajah dengan Implementasi Adaptif Threshold- Integral Image

2021 ◽  
Vol 8 (5) ◽  
pp. 919
Author(s):  
Maryam Ummul Habibah ◽  
Muchamad Kurniawan
Keyword(s):  
Adaptive Threshold ◽  
Image Resolution ◽  
Image Method ◽  
Threshold Parameter ◽  
Integral Image ◽  
Local Thresholding ◽  
Face Segmentation ◽  
The Face ◽  
Parameter Values ◽  
Indoor And Outdoor

<p>Segmentasi wajah merupakan bagian penting dalam pengolahan citra digital untuk mengetahui objek wajah dalam citra sebelum dilakukan pendeteksian ekspresi wajah. Adaptif <em>Threshold – Integral Image</em> adalah salah satu teknik segmentasi berbasis <em>pixel-based</em>,<em> </em>yaitu <em>local thresholding</em>. Penelitian ini bertujuan untuk memisahkan objek wajah manusia dan <em>background </em>-nya. Citra wajah yang akan digunakan nanti citra di dalam ruangan (<em>indoor</em>)<em> </em>dan di luar ruangan (<em>outdoor</em>) dengan resolusi gambar 300x400 piksel. Pada penelitian ini juga mencari nilai parameter S (<em>kernel</em>) dan T (<em>threshold</em>) yang terbaik dengan melakukan 16 kali percobaan. Dan didapatkan hasil terbaik, yaitu citra di dalam ruangan (<em>indoor</em>) nilai S=1/2 dan T=50, serta citra di luar ruangan (<em>outdoor</em>) nilai S=1/30 dan T=30. Segmentasi citra wajah dengan menggunakan metode Adaptif <em>Threshold – Integral Image</em> <em>robust</em> (kuat) terhadap intensitas cahaya tinggi dan rendah dengan mengatur nilai parameter S (<em>kernel</em>) dan T (<em>Threshold</em>) maka metode ini mampu memisahkan objek wajah dan <em>background</em> -nya. Dari hasil uji coba <em>threshold</em> menggunakan metode Adaptif <em>Threshold – Integral Image</em> terhadap citra di dalam ruangan (<em>indoor)</em> dan di luar ruangan (<em>outdoor)</em> menghasilkan <em>thresholding</em> yang baik dengan mempertimbangkan nilai parameter S (<em>kernel</em>) dan T (<em>threshold</em>) memberikan hasil dengan tingkat akurasi yang tinggi, yaitu citra di dalam ruangan (<em>indoor</em>) sebesar 96.72%, dan citra di luar ruangan (<em>outdoor</em>) sebesar 93.59%.</p><p> </p><p><em><strong>Abstract</strong></em></p><p><em>Face segmentation is an important in digital image processing to find out the object's face in the image before detecting facial expressions. Adaptive Threshold - Integral Image is a pixel-based segmentation technique, which is local thresholding. This study is intended to split the object of a human face and its background. Face images that will be used later in indoor and outdoor with an image resolution of 300x400 pixels. This study also searched for the best S (kernel) and T (threshold) parameter values by performing 16 experiments. And the best results are obtained, name the image in the room (indoor) the value of S = 1/2 and T = 50, and the image outside the room (outdoor) the value of S = 1/30 and T = 30. Face image segmentation using the Adaptive Threshold - Integral Image robust method of high and low light intensity by setting the S (kernel) and T (Threshold) parameter values, this method is able to split the face object and its background. From the results of the threshold trial using the Adaptive Threshold - Integral Image method for indoor and outdoor images produces a good thresholding by considering the values of the S (kernel) and T (threshold) parameters to give results with a high degree of accuracy, that is indoor images of 96.72%, and outdoor images of 93.59%.<strong></strong></em></p><p><em><strong><br /></strong></em></p>

Design of an Epicyclic Transmission for Speed Control of a Turbine-Generator System

1992 ◽  
Author(s):  
Indranil Barman ◽  
Donald R. Flugrad
Keyword(s):  
Control Method ◽  
Equations Of Motion ◽  
Speed Control ◽  
Gear Train ◽  
Turbine Generator ◽  
Generator System ◽  
Epicyclic Gear ◽  
The Face ◽  
Fine Control ◽  
Parameter Values

Abstract An improved speed control method is proposed for a turbine-generator system. Whereas the present method employs a steam valve to control the flow of steam according to the desired output, the proposed system uses an epicyclic gear train to provide fine control of the speed, while coarse control is still maintained through the steam valve. The systematic design of such a gear train is the objective of this project. Two configurations are considered as suitable candidates. After the transmissions are analyzed to obtain the speed and torque relations, the dynamic equations of motion and control equations for the systems are derived for simulation purposes. The simulations are then conducted for various load cases and parameter values to determine a suitable design for application in the power industry. The final configuration allows constant generator output speeds to be reliably maintained in the face of significant load disturbances.

The Stern Review on Climate Change: Inconvenient Sensitivities

2009 ◽  
Vol 20 (5) ◽  
pp. 779-798 ◽  
Author(s):  
Sergey Mityakov ◽  
Christof Rühl
Keyword(s):  
Climate Change ◽  
Time Preference ◽  
Complex Problem ◽  
Policy Choices ◽  
Subjective Judgement ◽  
The Face ◽  
Stern Review ◽  
The Cost ◽  
Parameter Values ◽  
Considerable Discussion

Nicholas Stern's Review of “The Economics of Climate Change” (2007) triggered considerable discussion, essentially by condensing a complex problem – the question of how to act in the face of global warming – into juxtaposing two numbers, the cost of mitigation and the cost of climate change. The Review concludes that mitigation today is economically superior to adaptation tomorrow. The review was widely criticized for the assumption of a pure rate of time preference of almost zero, on which its conclusions seemed to depend. In this paper we argue first, that this assumption discriminates against current in favour of future generations. Second, we perform a sensitivity analysis to test for the extent to which the conclusions of the Review are indeed based on the assumption of a rate of time preference of almost zero. We demonstrate that the conclusions of the Review are no longer valid as soon as parameter values are used which are standard in economic analysis. Combined, these results raise a bigger question: how wise is it to base crucial policy choices on a model so dependent on a single, deeply subjective, judgement call?

COLOR FACE SEGMENTATION USING A FUZZY MIN-MAX NEURAL NETWORK

2002 ◽  
Vol 02 (04) ◽  
pp. 587-601
Author(s):  
JUAN WACHS ◽  
HELMAN STERN ◽  
MARK LAST
Keyword(s):  
Neural Network ◽  
Color Model ◽  
Test Cases ◽  
Difficult Case ◽  
Automated Method ◽  
Hsv Color Model ◽  
Face Segmentation ◽  
The Face ◽  
Feature Information ◽  
Large Background

This work presents an automated method of segmentation of faces in color images with complex backgrounds. Segmentation of the face from the background in an image is performed by using face color feature information. Skin regions are determined by sampling the skin colors of the face in a Hue Saturation Value (HSV) color model, and then training a fuzzy min-max neural network (FMMNN) to automatically segment these skin colors. This work appears to be the first application of Simpson's FMMNN algorithm to the problem of face segmentation. Results on several test cases showed recognition rates of both face and background pixels to be above 93%, except for the case of a small face embedded in a large background. Suggestions for dealing with this difficult case are proffered. The image pixel classifier is linear of order O(Nh) where N is the number of pixels in the image and h is the number of fuzzy hyperbox sets determined by training the FMMNN.

scholarly journals How Should Cancer Models Be Constructed?

2020 ◽  
Vol 27 (1) ◽  
pp. 107327482096200
Author(s):  
Robert A. Beckman ◽  
Irina Kareva ◽  
Frederick R. Adler
Keyword(s):  
Complex Dynamics ◽  
Full Range ◽  
Evolutionary Game ◽  
Treatment Strategies ◽  
Predator Prey ◽  
Cancer Models ◽  
The Face ◽  
Predator Prey Models ◽  
The Right ◽  
Parameter Values

Choosing and optimizing treatment strategies for cancer requires capturing its complex dynamics sufficiently well for understanding but without being overwhelmed. Mathematical models are essential to achieve this understanding, and we discuss the challenge of choosing the right level of complexity to address the full range of tumor complexity from growth, the generation of tumor heterogeneity, and interactions within tumors and with treatments and the tumor microenvironment. We discuss the differences between conceptual and descriptive models, and compare the use of predator-prey models, evolutionary game theory, and dynamic precision medicine approaches in the face of uncertainty about mechanisms and parameter values. Although there is of course no one-size-fits-all approach, we conclude that broad and flexible thinking about cancer, based on combined modeling approaches, will play a key role in finding creative and improved treatments.

New FCM Segmentation Approach Based on Multi-Resolution Analysis

2018 ◽  
Vol 7 (4) ◽  
pp. 100-114
Author(s):  
Yaghmorasan Benzian ◽  
Nacéra Benamrane
Keyword(s):  
Fuzzy Clustering ◽  
Image Resolution ◽  
Pixel Classification ◽  
Resolution Image ◽  
Fuzzy C Means ◽  
Multi Resolution Analysis ◽  
Segmentation Approach ◽  
Resolution Analysis ◽  
Homogeneous Regions ◽  
Parameter Values

This article presents a modified Fuzzy C Means segmentation approach based on multi-resolution image analysis. Fuzzy C-Means standard methods are improved through fuzzy clustering at different image resolution levels by propagating fuzzy membership values pyramidally from a lower to a higher level. Processing at a lower resolution image level provides a rough pixel classification result, thus, a pixel is assigned to a cluster to which the majority of its neighborhood pixels belongs. The aim of fuzzy clustering with multi-resolution images is to avoid pixel misclassification according to the spatial cluster of the neighbourhood of each pixel in order to have more homogeneous regions and eliminate noisy regions present in the image. This method is tested particularly on samples and medical images with gaussian noise by varying multiresolution parameter values for better analysis. The results obtained after multi-resolution clustering are giving satisfactory results by comparing this approach with standard FCM and spatial FCM ones.

An arm neon optimised image abstraction method utilising the cosine integral image method

2014 ◽  
Author(s):  
Ryan Mark Gibson ◽  
David John James Round ◽  
Mark David Jenkins ◽  
Peter Barrie ◽  
Gordon Morison
Keyword(s):  
Image Method ◽  
Integral Image ◽  
Image Abstraction

scholarly journals Recovery of latent fingermarks from burial environments

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yam Tze Yong ◽  
Yusmazura Zakaria ◽  
Nik Fakhuruddin Nik Hassan
Keyword(s):  
Law Enforcement ◽  
Peat Soil ◽  
Law Enforcement Agencies ◽  
Metal Substrates ◽  
Realistic Situation ◽  
Crime Scene Investigators ◽  
The Face ◽  
Oil Red O ◽  
Indoor And Outdoor

Abstract Background Fingermarks can be found both in indoor and outdoor crime scenes. The latter could be subjected to various types of environmental insults. In many cases, criminals try to dispose of or conceal the evidence in several ways, such as throwing in the waterways or burying in the soil to avoid detection from the law enforcement agencies. Thus, crime scene investigators often face challenges to detect and develop latent fingermarks in such environments. This study aimed to investigate the persistence and ageing of latent fingermarks in a burial environment for particular periods. To date, there is a limited study that attempted to investigate the survivability of fingermarks in a burial environment. Methodology The experiment was carried out in two settings: preliminary and main experiments. A preliminary experiment was conducted indoor to determine the most effective chemical for fingermark development on buried metal substrates. Five different chemicals were employed to develop the latent fingermarks, namely fingermark powder dusting, small particle reagent (SPR), Sudan black, oil red O, and crystal violet. The main experiment was carried out to simulate the realistic situation in which the metal substrates bearing latent fingermarks were buried in the soil within 2 months period. In both experiments, the substrates were buried in peat soil at a depth of 10 cm from the surface. Results The results demonstrated that latent fingermarks could be effectively recovered after being buried in the soil up to 8 weeks using Sudan black. The position of the substrates whether underlying in “face up” or “face down” orientations when buried had also influenced the quality of the developed fingermarks. Fingermarks buried in the “face up” position demonstrated better quality and more ridge details as compared to those buried in the “face down” position. Secondary fingermarks were also observed in this study and found to be useful for identification and must be taken into consideration when developing fingermarks on buried items in forensic cases. Conclusion The development of fingermarks recovered from burial environments is feasible as excellent ridge characteristics can still be identified. Hence, any evidence recovered from burial sites should be examined for fingermarks and cannot be discounted.

scholarly journals Pengaplikasian Face Recognition 3 Dimensi Untuk Keamanan

2020 ◽  
Vol 12 (1) ◽  
pp. 35-39
Author(s):  
Jason Adrian Mahalim ◽  
Muhamad Aliefian Rahmatulloh ◽  
Muhamad Rizky Febrianto ◽  
Nabila Husna Shabrina
Keyword(s):  
Face Recognition ◽  
Recognition Accuracy ◽  
Image Resolution ◽  
Face Alignment ◽  
3 Dimensional ◽  
Security Measure ◽  
The Face ◽  
Door Lock ◽  
Dimensional Face

Face recognition is one of the biometric categories which uses face as the identifier. Currently, there are two versions of face recognition, 2 dimensional and 3 dimensional. This research uses 3 dimensional face recognition, and the goal for this research is for comparing the accuracy between 2 dimensional and 3 dimensional face recognition, analyze the performance of 3 dimensional face recognition, and applying 3dimensional face recognition for security measure, namely for automatic door lock using face recognition. Face Alignment Network used as the method for this 3 dimensional face recognition. This research prove that 3 dimensional face recognition have better accuracy than its predecessor, however some weakness is also found in this research, i.e. image resolution, lighting of the photo, angle of the face when the photo taken will govern the accuracy of the 3 dimensional face recognition and 3 dimensional face recognition can’t differentiatebetween twins brother faces.Key word : Face recognition, accuracy

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