Mummified Dead Body in Hanging Position: A Case Report

Mummification refers to all-natural and artificial processes that bring about the preservation of the body or its parts. Such processes include mainly the drying of the soft tissues instead of liquefying putrefaction. We are presenting here a case of a medicolegal autopsy performed at the mortuary of MGIMS, Sevagram. The body was found in the jungle in a hanging position to the branch of a tree. Body was completely mummified. Facial identification could be made out as facial features were well maintained. Investigation agency has query regarding condition of the body (mummification) and what is the time since death. After performing the autopsy, police were explained regarding the factors responsible for mummification to occur in the dead body and also given opinion regarding time since death. From the time since death police investigated the various missing complaints which were present at neighboring police stations during that period. So the relatives from one of the missing person identified the body and it was handed over to relative after completion of all legal formalities by the police officials. In this case report we have discussed; autopsy finding in mummified body and factors responsible for formation mummification of the body. Hot, dry and airy environment are well known factors contributing the mummification of body but apart from this hanging of the body along with other contributing factors mentioned earlier is responsible for mummification of the body in present case.

A New Method Using Naive Bayes And RGBD Facial Identification Based on Extracted Features from Image Pixels

Nowadays, life seems to have been resilient, particularly for those with physical disabilities. Recognition of AV letters is one of the critical and famously the difficult structures. This research has been developed based on the potential of the features in some applications than the statistical properties. While, these features have been resolved the lip movement for AV letters recognition, Naive Bayesian and Red green blue and depth RGBD have been adopted for visual letter identification. Naive Bayesian has 73.33% for usual recognition with three letters, each with ten frames, while RGBD classifier is 100%. Within that for this case, two scenarios were made with different forms of noise placed on the face of normal, normal + 10%, normal + 25% and normal + 75% noise. The first one trains and understands all classes, one after another. While the other is training 95 percent of RGBD and 83.3 percent for Naive Bayesian with recognition of one of the inflicted forms. RGBD identification is 100 percent for the second one, while 49.99 for the Naive Bayesian.

Smart Door for Handicapped People via Face Recognition and Voice Command Technique

Smart home indicates an application for different technological implementations, it could indicate any system which controls the door lock and several other devices. Facial identification which is an important section to achieve surveillance and safety, especially for handicapped people, can be considered as one of the ways that deal with biometrics and performed to identify facial images via utilizing fundamental features of the face. A Raspberry Pi-based face recognition system using conventional face detection and recognition techniques is going to be supplied, so the method in which image-built biometrics uses a Raspberry Pi is described. The aim of the paper here can be considered as transferring face recognition to a level in which the system can replace the utilizing of RF I-Cards and a password to access any system of security and making the system alive and protect the door from being open by hackers, especially by using the picture of an authorized person, we make the raspberry pi turn off and cannot turn on only by a command from the authorized person's mobile. The result of the presented proposal is a system that uses face recognition by utilizing OpenCV, Raspberry Pi, and it functions on an application of Android, and this system percentage becomes 99.63%. It should be cost-effective, of high performance, secured, and easy to use, which can be used in any smart home application.

CURRENT STAGE OF DEVELOPMENT OF PERSONALITY IDENTIFICATION EXAMINATION BASED ON APPEARANCE (FACIAL IDENTIFICATION)

The article presents the results of a theoretical analysis of the current state of examination of personality identification based on appearance. The question of changing the object of research in the specified examination was raised. It has been established that with the development of digital technologies, multi-angle facial images began to prevail as an object of research, and studies of video recordings are widespread. The different position of the head in the studied images led to the impossibility of using a significant number of comparative research methods: alignment along the medial line, alignment along a broken line, image editing, applications, “masks”, overlaying translucent images, comparison of relative values, overlay of coordinate grids, construction of geometric shapes. The transformation of research objects necessitates a change in the methods of comparative research. It is indicated that with the proliferation of video images, the identification capabilities of the examination have increased: an expert can examine images of an identifiable person on the entire video sequence. A common disadvantage of video recordings is image quality. For research, video recordings from external video surveillance cameras are often received, but the purpose of installing such cameras is to fix the environment, and not the faces of people. This explains the poor image quality. A frequent problem in carrying out examinations for the identification of a person by signs of appearance is the “recognition effect”. At the first glance at the image, one may get the impression that it is suitable for identification in the framework of portrait examination. However, this impression is most often mistaken. Often people have a sense of the obviousness of the image of a particular person in the frame if they have experience of interaction with this person. In addition, upon a detailed study of the image, an expert may conclude that it is unusable. The captured signs of appearance do not always constitute the necessary complex for the possibility of conducting research. The current state of examination in identifying a person based on appearance suggests the need to develop comparison methods that could take into account the difference in the angles of the people under study. These methods include a graphical identification algorithm, a method of dimensional ratios of individual elements of appearance, and mathematical research methods. Further development in these areas is promising for expanding the possibilities of carrying out facial identification.

Simulation of English classroom effectiveness based on human-computer interaction and facial identification

A variety of factors affect English classroom teaching, which prevents teachers from effectively grasping students’ learning status and learning situation. In particular, classroom management is more difficult during online teaching. In order to improve the effectiveness of English classroom teaching, based on the human-computer interaction algorithm and facial identification algorithm, this paper effectively recognizes the human-computer interaction process and classroom learning status of students in online teaching, and eliminates the image background according to the actual teaching needs. Moreover, by extracting and fusing the time sequence information and spatial information of the motion in the video, a spatiotemporal feature image capable of expressing a dynamic typical feature is obtained. In addition, this paper uses system algorithms to judge the status and feed back the identification results to the teacher’s teaching terminal equipment, which is convenient for timely teaching adjustment. Finally, this paper analyzes the effectiveness of the algorithm through simulation experiments. The research results show that the algorithm constructed in this paper has good performance.

RADIO FREQUENCY IDENTIFICATION AND IMAGE-BASED FACIAL IDENTIFICATION AS AN EMPLOYEE ATTENDANCE SYSTEM

The current development of microcontroller technology can be used to build a presence system for employees. The employee attendance system uses radio frequency identification and facial identification which is designed and built to make it easier to do attendance data recording, so that the data obtained can be precise and accurate. Data collection techniques, namely by interview and observation. The application development process uses the PHP and Python programming languages ​​with Visual Studio Code software applications, Arduino Uno, MySQL software as a database server, and XAMPP as a support. The input used in this system is the employee's personal data and the results of employee face data retrieval which are stored in the .jpg format. The faces taken were taken from 4 people where each face was taken 20 face samples. The results are in the form of web and applications that will provide solutions to existing problems. The conclusion of this application makes it easy to do the recording and attendance, and minimize the fraud committed by employees. Retrieval of face data was taken as much as 20 data with the highest level of accuracy was 87% when the presence test was carried out.

Body Language Influences on Facial Identification at Passport Control: An Exploration in Virtual Reality

Person identification at airports requires the matching of a passport photograph to its bearer. One aim of this process is to find identity impostors, who use valid identity documents of similar-looking people to avoid detection. In psychology, this process has been studied extensively with static pairs of face photographs that require identity match (same person shown) versus mismatch (two different people) decisions. However, this approach provides a limited proxy for studying how other factors, such as nonverbal behaviour, affect this task. The current study investigated the influence of body language on facial identity matching within a virtual reality airport environment, by manipulating activity levels of person avatars queueing at passport control. In a series of six experiments, detection of identity mismatches was unaffected when observers were not instructed to utilise body language. By contrast, under explicit instruction to look out for unusual body language, these cues enhanced detection of mismatches but also increased false classification of matches. This effect was driven by increased activity levels rather than body language that simply differed from the behaviour of the majority of passengers. The implications and limitations of these findings are discussed.