Detection Of Feature In A Face Image Using Digital Image Processing Using Matlab

In the paper, an enhanced a daboost algorithm is suggested for enhancement of performance of system. In this algorithm, the eigenvectors are computed for the facial space & classification is implemented. In the classification, we underwent the process of learning for training & testing. On that basis, the facial expressions are identified. As from the outcomes of session in base paper, the outcomes are obtained from reboost detection. The outcomes are provided for false alarm rate & Detection rate. The suggested methodology is implemented & performance for detection rate is also improvised for false alarm rate also. The rte of detection is also enhanced & false alarm rate is minimized. For presenting the contrast, a GUI window is presented in which the contrast is displayed

Deteksi Jerawat Pada Wajah Menggunakan Metode Viola Jones

Acne is a skin disease that most often grow in the face and very disruptive to affect the appearance of a person's face. Viola Jones is one method to help detect acne so someone get information about the state of the face and immediately overcome. Viola Jones Method has three main processes integral image is used to determine whether there is a feature haar particular in an image, the method adaboost machine learning is used to select features haar specific that will be used to adjust the threshold value, and a cascade classifier as the classification of the final determining regions the face in the picture. Testing of 30 samples, the results obtained showed that the method is less accurate Viola Jones is used as a method of detection of acne with results average 25 % the percentage of common acne, blackheads 0 % and 45% of cystic acne. The number of samples used to create xml greatly affect the results of detection

Smart Attendance Monitoring System Using Face Registering

Face recognition is one of the main branches of biometric verification as the face is the identity of an individual and it is utilized by many organizations to mark attendance of employees. Currently student attendance is recorded physically in the classroom by calling their unique ids, which utilizes more time and it is tedious to verify and identify each student if the number of students increases beyond normal range and it is tough to cross verify whether the authenticated students are actually responding. This project demonstrates a technique for attendance monitoring with facial recognition method by using two different algorithms one will be the existing algorithm such as Principal Component Analysis (PCA) algorithm and the other one is proposed by us which is Unconstrained FACE REGISTERING ALGORITHM. This method will automatically record the attendance of the scholars who are present in the classroom and it will also maintain a login and logout time of students and faculties and administration can easily access all the data of the students. However, it is difficult to estimate the outcome of facial recognition as most of the systems currently present have low detection rate and takes 20-100 images of a person for better identification. In this project attendance is marked by continuous observation which helps the system to improve and it also eliminates few features which affects the performance of the system that are different poses, light effects, partial occlusion etc. which helps the system to achieve better accuracy. This method will save approx 15-20 min of valuable class time and can be used to interact or clear doubts with teachers

The Implementation of Augmented Reality Hairstyles at Beauty Salons Using the Viola-Jones Method (Case Study: Eka Salon)

Augmented reality is the technology that superimposes a computer-generated digital content on a user's view of the real world in a real time so users can experience the real virtual objects. The use of augmented reality has spread into various industries, for an example in the fashion industry. One of fashion industry type is hairstyle industry. Eka Salon is a beauty salon that provides beauty treatments for women's hair care. This salon has a problem that customer are not satisfacted with the results of their new haircut because that doesnt match with their expectations. This can be seen from the results of observations at Eka Salon is resulted that 8 out of 15 interviewed customers were not satisfied with their new haircuts because it did not match the appearance in the catalog. In this research, an augmented reality hairstyles will be made that can visualize how the shape of the selected hairstyle by the customer without having to cut their hair first. The Viola-Jones method was chosen as the method used in this study because it has a high accuracy of 90% in face detection. The result of this research is that the Viola-Jones method can detect facial surfaces and generate a 3D hairstyle model distance to 100cm properly. The test of the acceptance level of this application is carried out by Eka Salon customers with an average percentage of 84.3%

Business and Social Behaviour Intelligence Analysis Using PSO

The goal of this paper is to elaborate swarm intelligence for business intelligence decision making and the business rules management improvement. The paper introduces the decision making model which is based on the application of Artificial Neural Networks (ANNs) and Particle Swarm Optimization (PSO) algorithm. Essentially the business spatial data illustrate the group behaviors. The swarm optimization, which is highly influenced by the behavior of creature, performs in group. The Spatial data is defined as data that is represented by 2D or 3D images. SQL Server supports only 2D images till now. As we know that location is an essential part of any organizational data as well as business data: enterprises maintain customer address lists, own property, ship goods from and to warehouses, manage transport flows among their workforce, and perform many other activities. By means to say a lot of spatial data is used and processed by enterprises, organizations and other bodies in order to make the things more visible and self-descriptive. From the experiments, we found that PSO is can facilitate the intelligence in social and business behaviour

An Effective Approach for Mobile ad hoc Network via I-Watchdog Protocol

Mobile ad hoc network (MANET) is now days become very famous due to their fixed infrastructure-less quality and dynamic nature. They contain a large number of nodes which are connected and communicated to each other in wireless nature. Mobile ad hoc network is a wireless technology that contains high mobility of nodes and does not depend on the background administrator for central authority, because they do not contain any infrastructure. Nodes of the MANET use radio wave for communication and having limited resources and limited computational power. The Topology of this network is changing very frequently because they are distributed in nature and self-configurable. Due to its wireless nature and lack of any central authority in the background, Mobile ad hoc networks are always vulnerable to some security issues and performance issues. The security imposes a huge impact on the performance of any network. Some of the security issues are black hole attack, flooding, wormhole attack etc. In this paper, we will discuss issues regarding low performance of Watchdog protocol used in the MANET and proposed an improved Watchdog mechanism, which is called by I-Watchdog protocol that overcomes the limitations of Watchdog protocol and gives high performance in terms of throughput, delay

An Effective Approach for Mobile ad hoc Network via I-Watchdog Protocol

Mobile ad hoc network (MANET) is now days become very famous due to their fixed infrastructure-less quality and dynamic nature. They contain a large number of nodes which are connected and communicated to each other in wireless nature. Mobile ad hoc network is a wireless technology that contains high mobility of nodes and does not depend on the background administrator for central authority, because they do not contain any infrastructure. Nodes of the MANET use radio wave for communication and having limited resources and limited computational power. The Topology of this network is changing very frequently because they are distributed in nature and self-configurable. Due to its wireless nature and lack of any central authority in the background, Mobile ad hoc networks are always vulnerable to some security issues and performance issues. The security imposes a huge impact on the performance of any network. Some of the security issues are black hole attack, flooding, wormhole attack etc. In this paper, we will discuss issues regarding low performance of Watchdog protocol used in the MANET and proposed an improved Watchdog mechanism, which is called by I-Watchdog protocol that overcomes the limitations of Watchdog protocol and gives high performance in terms of throughput, delay