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Thematische Bibliographien / Face detection on thermal image / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „Face detection on thermal image“

Autor: Grafiati

Veröffentlicht am 28. Juni 2021

Zuletzt aktualisiert am 1. Februar 2022

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Seo, Jongwoo, and In-Jeong Chung. "Face Liveness Detection Using Thermal Face-CNN with External Knowledge." Symmetry 11, no. 3 (2019): 360. http://dx.doi.org/10.3390/sym11030360.

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Face liveness detection is important for ensuring security. However, because faces are shown in photographs or on a display, it is difficult to detect the real face using the features of the face shape. In this paper, we propose a thermal face-convolutional neural network (Thermal Face-CNN) that knows the external knowledge regarding the fact that the real face temperature of the real person is 36~37 degrees on average. First, we compared the red, green, and blue (RGB) image with the thermal image to identify the data suitable for face liveness detection using a multi-layer neural network (MLP

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Albar, Albar, Hendrick Hendrick, and Rahmad Hidayat. "Segmentation Method for Face Modelling in Thermal Images." Knowledge Engineering and Data Science 3, no. 2 (2020): 99. http://dx.doi.org/10.17977/um018v3i22020p99-105.

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Face detection is mostly applied in RGB images. The object detection usually applied the Deep Learning method for model creation. One method face spoofing is by using a thermal camera. The famous object detection methods are Yolo, Fast RCNN, Faster RCNN, SSD, and Mask RCNN. We proposed a segmentation Mask RCNN method to create a face model from thermal images. This model was able to locate the face area in images. The dataset was established using 1600 images. The images were created from direct capturing and collecting from the online dataset. The Mask RCNN was configured to train with 5 epoc

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Ma, Chao, Ngo Trung, Hideaki Uchiyama, Hajime Nagahara, Atsushi Shimada, and Rin-ichiro Taniguchi. "Adapting Local Features for Face Detection in Thermal Image." Sensors 17, no. 12 (2017): 2741. http://dx.doi.org/10.3390/s17122741.

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Kowalski, Marcin, and Krzysztof Mierzejewski. "Detection of 3D face masks with thermal infrared imaging and deep learning techniques." Photonics Letters of Poland 13, no. 2 (2021): 22. http://dx.doi.org/10.4302/plp.v13i2.1091.

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Biometric systems are becoming more and more efficient due to increasing performance of algorithms. These systems are also vulnerable to various attacks. Presentation of falsified identity to a biometric sensor is one the most urgent challenges for the recent biometric recognition systems. Exploration of specific properties of thermal infrared seems to be a comprehensive solution for detecting face presentation attacks. This letter presents outcome of our study on detecting 3D face masks using thermal infrared imaging and deep learning techniques. We demonstrate results of a two-step neural ne

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Cho, Se, Na Baek, Min Kim, Ja Koo, Jong Kim, and Kang Park. "Face Detection in Nighttime Images Using Visible-Light Camera Sensors with Two-Step Faster Region-Based Convolutional Neural Network." Sensors 18, no. 9 (2018): 2995. http://dx.doi.org/10.3390/s18092995.

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Conventional nighttime face detection studies mostly use near-infrared (NIR) light cameras or thermal cameras, which are robust to environmental illumination variation and low illumination. However, for the NIR camera, it is difficult to adjust the intensity and angle of the additional NIR illuminator according to its distance from an object. As for the thermal camera, it is expensive to use as a surveillance camera. For these reasons, we propose a nighttime face detection method based on deep learning using a single visible-light camera. In a long-distance night image, it is difficult to dete

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Latinović, Nikola, Tijana Vuković, Ranko Petrović, et al. "Implementation challenge and analysis of thermal image degradation on R-CNN face detection." Telfor Journal 12, no. 2 (2020): 98–103. http://dx.doi.org/10.5937/telfor2002098l.

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Face detection systems with color cameras were rapidly evolving and have been well researched. In environments with good visibility they can reach excellent accuracy. But changes in illumination conditions can result in performance degradation, which is the one of the major limitations in visible light face detection systems. The solution to this problem could be in using thermal infrared cameras, since their operation doesn't depend on illumination. Recent studies have shown that deep learning methods can achieve an impressive performance on object detection tasks, and face detection in parti

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Fitriyah, Hurriyatul, and Edita Rosana Widasari. "Face Detection of Thermal Images in Various Standing Body-Pose using Facial Geometry." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 14, no. 4 (2020): 407. http://dx.doi.org/10.22146/ijccs.59672.

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Automatic face detection in frontal view for thermal images is a primary task in a health system e.g. febrile identification or security system e.g. intruder recognition. In a daily state, the scanned person does not always stay in frontal face view. This paper develops an algorithm to identify a frontal face in various standing body-pose. The algorithm used an image processing method where first it segmented face based on human skin’s temperature. Some exposed non-face body parts could also get included in the segmentation result, hence discriminant features of a face were applied. The shape

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van Doremalen, Rob F. M., Jaap J. van Netten, Jeff G. van Baal, Miriam M. R. Vollenbroek-Hutten, and Ferdinand van der Heijden. "Infrared 3D Thermography for Inflammation Detection in Diabetic Foot Disease: A Proof of Concept." Journal of Diabetes Science and Technology 14, no. 1 (2019): 46–54. http://dx.doi.org/10.1177/1932296819854062.

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Background: Thermal assessment of the plantar surface of the foot using spot thermometers and thermal imaging has been proven effective in diabetic foot ulcer prevention. However, with traditional cameras this is limited to single spots or a two-dimensional (2D) view of the plantar side of foot, where only 50% of the ulcers occur. To improve ulcer detection, the view has to be extended beyond 2D. Our aim is to explore for proof of concept the combination of three-dimensional (3D) models with thermal imaging for inflammation detection in diabetic foot disease. Method: From eight participants wi

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Bedoya-Echeverry, Sebastián, Hernán Belalcázar-Ramírez, Humberto Loaiza-Correa, Sandra Esperanza Nope-Rodríguez, Carlos Rafael Pinedo-Jaramillo, and Andrés David Restrepo-Girón. "Detection of lies by facial thermal imagery analysis." Revista Facultad de Ingeniería 26, no. 44 (2017): 45. http://dx.doi.org/10.19053/01211129.v26.n44.2017.5771.

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An artificial vision system is presented for lie detection by analyzing face thermal image sequences. This system represents an alternative technique to the polygraph. Some of its features are: 1) it has no physical contact with the examinee, 2) it is non-intrusive, 3) it has a potential for private use, and 4) it can simultaneously analyze several persons. The proposed system is based on the detection of physiological changes in temperature in the lacrimal puncta area caused by the subtle increase in blood flow through the nearby vascular network. These changes take place when anxiety appears

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Kopaczka, Marcin, Lukas Breuer, Justus Schock, and Dorit Merhof. "A Modular System for Detection, Tracking and Analysis of Human Faces in Thermal Infrared Recordings." Sensors 19, no. 19 (2019): 4135. http://dx.doi.org/10.3390/s19194135.

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We present a system that utilizes a range of image processing algorithms to allow fully automated thermal face analysis under both laboratory and real-world conditions. We implement methods for face detection, facial landmark detection, face frontalization and analysis, combining all of these into a fully automated workflow. The system is fully modular and allows implementing own additional algorithms for improved performance or specialized tasks. Our suggested pipeline contains a histogtam of oriented gradients support vector machine (HOG-SVM) based face detector and different landmark deteci

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Marzec, Mariusz, Robert Koprowski, Zygmunt Wróbel, Agnieszka Kleszcz, and Sławomir Wilczyński. "Automatic method for detection of characteristic areas in thermal face images." Multimedia Tools and Applications 74, no. 12 (2013): 4351–68. http://dx.doi.org/10.1007/s11042-013-1745-9.

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Nata Septiadi, Wayan, Ni Made Dian Sulistiowati, and Abdul Wakhid. "THERMOGRAPHIC EVALUATION FOR THE DIVERSE STAGE OF ANXIETY ON FACE TEMPERATURE AT FRONTAL AND TEMPORAL USING THERMAL IMAGING." Humanities & Social Sciences Reviews 7, no. 5 (2019): 1130–36. http://dx.doi.org/10.18510/hssr.2019.75149.

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that it is able to provide accurate results about the temperature picture. The purpose of this study was to examine if there were differences in anxiety conditions at facial temperatures measured using thermal imaging. Methodology: Eighty-one participants were taking the pre-clinical exams was chosen as the inclusion criteria and were divided into four categories of anxiety range (not anxious, mild anxiety, moderate anxiety, and severe anxiety) based on their score measured that using the General Anxiety Disorder (GAD-7) as the instrument. The participants were measured their face temper

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Sun, Pengcheng, Dan Zeng, Xiaoyan Li, et al. "A 3D Mask Presentation Attack Detection Method Based on Polarization Medium Wave Infrared Imaging." Symmetry 12, no. 3 (2020): 376. http://dx.doi.org/10.3390/sym12030376.

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Facial recognition systems are often spoofed by presentation attack instruments (PAI), especially by the use of three-dimensional (3D) face masks. However, nonuniform illumination conditions and significant differences in facial appearance will lead to the performance degradation of existing presentation attack detection (PAD) methods. Based on conventional thermal infrared imaging, a PAD method based on the medium wave infrared (MWIR) polarization characteristics of the surface material is proposed in this paper for countering a flexible 3D silicone mask presentation attack. A polarization MW

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Rao, M. Sivasankara, K. Tejasree, P. Sathwik, P. Sandeep Kumar, and M. Sailohith. "Real Time Face Mask Detection and Thermal Screening with Audio Response for COVID-19." Revista Gestão Inovação e Tecnologias 11, no. 4 (2021): 2703–14. http://dx.doi.org/10.47059/revistageintec.v11i4.2311.

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The coronavirus COVID-19 pandemic is continuously spreading until now everywhere on the earth, and causing a severe health crisis. So the helpful and safe-keeping method is wearing a face mask in all areas where people are gathered, according to the World Health Organization (WHO). Along with the face mask, body temperature and sanitization also plays a vital role in being safer. Thus, monitoring the individuals that are wearing the mask or not is more significant. In this paper, we propose a system that uses TensorFlow, Keras, MobileNetV2, and OpenCV to detect the face mask. A dataset contain

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Kakaraparthi, Vimal, Qijia Shao, Charles J. Carver, et al. "FaceSense." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, no. 3 (2021): 1–27. http://dx.doi.org/10.1145/3478129.

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Face touch is an unconscious human habit. Frequent touching of sensitive/mucosal facial zones (eyes, nose, and mouth) increases health risks by passing pathogens into the body and spreading diseases. Furthermore, accurate monitoring of face touch is critical for behavioral intervention. Existing monitoring systems only capture objects approaching the face, rather than detecting actual touches. As such, these systems are prone to false positives upon hand or object movement in proximity to one's face (e.g., picking up a phone). We present FaceSense, an ear-worn system capable of identifying act

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Jakkaew, Prasara, and Takao Onoye. "Non-Contact Respiration Monitoring and Body Movements Detection for Sleep Using Thermal Imaging." Sensors 20, no. 21 (2020): 6307. http://dx.doi.org/10.3390/s20216307.

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Monitoring of respiration and body movements during sleep is a part of screening sleep disorders related to health status. Nowadays, thermal-based methods are presented to monitor the sleeping person without any sensors attached to the body to protect privacy. A non-contact respiration monitoring based on thermal videos requires visible facial landmarks like nostril and mouth. The limitation of these techniques is the failure of face detection while sleeping with a fixed camera position. This study presents the non-contact respiration monitoring approach that does not require facial landmark v

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Jamrozik, Wojciech, and Jacek Górka. "Detection of slag inclusions using infrared thermal imagining system." MATEC Web of Conferences 338 (2021): 01012. http://dx.doi.org/10.1051/matecconf/202133801012.

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Assuring high quality of welded joins is a vital task in many industrial branches also when joints are made manually. It is the case metal-arc welding with covered electrode. One of main imperfection, that can occur in this process is slag inclusion. In the paper an method for detection of slag inclusion in multipass manual welding is proposed and validated. The key idea of the method is that small temperature disturbances will be noticeable in consecutive cross-section of joint in the cooling pass. Temperature distribution weld face was measured with longwave infrared camera (LWIR). For conse

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Samadiani, Huang, Cai, et al. "A Review on Automatic Facial Expression Recognition Systems Assisted by Multimodal Sensor Data." Sensors 19, no. 8 (2019): 1863. http://dx.doi.org/10.3390/s19081863.

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Facial Expression Recognition (FER) can be widely applied to various research areas, such as mental diseases diagnosis and human social/physiological interaction detection. With the emerging advanced technologies in hardware and sensors, FER systems have been developed to support real-world application scenes, instead of laboratory environments. Although the laboratory-controlled FER systems achieve very high accuracy, around 97%, the technical transferring from the laboratory to real-world applications faces a great barrier of very low accuracy, approximately 50%. In this survey, we comprehen

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Rodriguez-Lozano, Francisco J., Fernando León-García, M. Ruiz de Adana, Jose M. Palomares, and J. Olivares. "Non-Invasive Forehead Segmentation in Thermographic Imaging." Sensors 19, no. 19 (2019): 4096. http://dx.doi.org/10.3390/s19194096.

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The temperature of the forehead is known to be highly correlated with the internal body temperature. This area is widely used in thermal comfort systems, lie-detection systems, etc. However, there is a lack of tools to achieve the segmentation of the forehead using thermographic images and non-intrusive methods. In fact, this is usually segmented manually. This work proposes a simple and novel method to segment the forehead region and to extract the average temperature from this area solving this lack of non-user interaction tools. Our method is invariant to the position of the face, and other

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Laureti, Stefano, Muhammad Khalid Rizwan, Hamed Malekmohammadi, et al. "Delamination Detection in Polymeric Ablative Materials Using Pulse-Compression Thermography and Air-Coupled Ultrasound." Sensors 19, no. 9 (2019): 2198. http://dx.doi.org/10.3390/s19092198.

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Ablative materials are used extensively in the aerospace industry for protection against high thermal stresses and temperatures, an example being glass/silicone composites. The extreme conditions faced and the cost-risk related to the production/operating stage of such high-tech materials indicate the importance of detecting any anomaly or defect arising from the manufacturing process. In this paper, two different non-destructive testing techniques, namely active thermography and ultrasonic testing, have been used to detect a delamination in a glass/silicone composite. It is shown that a frequ

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Rahman, MD Abdur, M. Shamim Hossain, Nabil A. Alrajeh, and B. B. Gupta. "A Multimodal, Multimedia Point-of-Care Deep Learning Framework for COVID-19 Diagnosis." ACM Transactions on Multimedia Computing, Communications, and Applications 17, no. 1s (2021): 1–24. http://dx.doi.org/10.1145/3421725.

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In this article, we share our experiences in designing and developing a suite of deep neural network–(DNN) based COVID-19 case detection and recognition framework. Existing pathological tests such as RT-PCR-based pathogen RNA detection from nasal swabbing seem to display low detection rates during the early stages of virus contraction. Moreover, the reliance on a few overburdened laboratories based around an epicenter capable of supplying large numbers of RT-PCR tests makes this testing method non-scalable when the rate of infections is high. Similarly, finding an effective drug or vaccine wit

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Zefri, Yahya, Achraf ElKettani, Imane Sebari, and Sara Ait Lamallam. "Thermal Infrared and Visual Inspection of Photovoltaic Installations by UAV Photogrammetry—Application Case: Morocco." Drones 2, no. 4 (2018): 41. http://dx.doi.org/10.3390/drones2040041.

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Being sustainable, clean, and eco-friendly, photovoltaic technology is considered as one of the most hoped solutions face to worldwide energetic challenges. Morocco joins this context with the inauguration of numerous clean energy projects. However, one key factor in making photovoltaic installations a profitable investment are regular and effective inspections in order to detect occurred defects. Unmanned aerial vehicles (UAV) are increasingly used in various inspection fields. In this respect, this work focuses on the use of thermal and visual imagery taken by UAV in the inspection of photov

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Negishi, Toshiaki, Shigeto Abe, Takemi Matsui, et al. "Contactless Vital Signs Measurement System Using RGB-Thermal Image Sensors and Its Clinical Screening Test on Patients with Seasonal Influenza." Sensors 20, no. 8 (2020): 2171. http://dx.doi.org/10.3390/s20082171.

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Background: In the last two decades, infrared thermography (IRT) has been applied in quarantine stations for the screening of patients with suspected infectious disease. However, the fever-based screening procedure employing IRT suffers from low sensitivity, because monitoring body temperature alone is insufficient for detecting infected patients. To overcome the drawbacks of fever-based screening, this study aims to develop and evaluate a multiple vital sign (i.e., body temperature, heart rate and respiration rate) measurement system using RGB-thermal image sensors. Methods: The RGB camera me

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Awhad, Rahul, Saurabh Jayswal, Adesh More, and Jyoti Kundale. "Fraudulent Face Image Detection." ITM Web of Conferences 32 (2020): 03005. http://dx.doi.org/10.1051/itmconf/20203203005.

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Due to the growing advancements in technology, many software applications are being developed to modify and edit images. Such software can be used to alter images. Nowadays, an altered image is so realistic that it becomes too difficult for a person to identify whether the image is fake or real. Such software applications can be used to alter the image of a person’s face also. So, it becomes very difficult to identify whether the image of the face is real or not. Our proposed system is used to identify whether the image of a face is fake or real. The proposed system makes use of machine learni

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Wen, Lilong, and Dan Xu. "Face Image Manipulation Detection." IOP Conference Series: Materials Science and Engineering 533 (May 30, 2019): 012054. http://dx.doi.org/10.1088/1757-899x/533/1/012054.

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Nam, Amir Nobahar Sadeghi. "Face Detection." Volume 5 - 2020, Issue 9 - September 5, no. 9 (2020): 688–92. http://dx.doi.org/10.38124/ijisrt20sep391.

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Face detection is one of the challenging problems in the image processing, as a main part of automatic face recognition. Employing the color and image segmentation procedures, a simple and effective algorithm is presented to detect human faces on the input image. To evaluate the performance, the results of the proposed methodology is compared with ViolaJones face detection method.

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Wei, Gang, and Ishwar K. Sethi. "Face detection for image annotation." Pattern Recognition Letters 20, no. 11-13 (1999): 1313–21. http://dx.doi.org/10.1016/s0167-8655(99)00100-2.

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Gaurav Melkani and Dr. Sunil Maggu. "Image-Based Face Detection and Recognition." International Journal for Modern Trends in Science and Technology 6, no. 12 (2021): 466–70. http://dx.doi.org/10.46501/ijmtst061290.

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Face recognition from image or video is a popular topic in biometrics research. Many public places usually have surveillance cameras for video capture and these cameras have their significant value for security purpose. It is widely acknowledgedthatthefacerecognitionhaveplayedanimportant role in surveillance system as it doesn’t need the object’s cooperation. The actual advantages of face based identification over other biometrics are uniqueness and acceptance. As human face is a dynamic object having high degree of variability in its appearance, that makes face detection a difficult problem i

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Muhimmah, Izzati, Fadhillah Abriyani, and Arrie Kurniawardhani. "Automatic wrinkles detection on face image." IOP Conference Series: Materials Science and Engineering 482 (March 11, 2019): 012026. http://dx.doi.org/10.1088/1757-899x/482/1/012026.

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Oualla, Mohamed, Khalid Ounachad, and Abdelalim Sadiq. "Building Face Detection with Face Divine Proportions." International Journal of Online and Biomedical Engineering (iJOE) 17, no. 04 (2021): 63. http://dx.doi.org/10.3991/ijoe.v17i04.19149.

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<p class="0abstract"><span lang="EN-US">In this paper, we proposed an algorithm for detecting multiple human faces in an image based on haar-like features to represent the invariant characteristics of a face. The choice of relevant and more representative features is based on the divine proportions of a face. This technique, widely used in the world of beauty, especially in aesthetic medicine, allows the face to be divided into a set of specific regions according to known mathematical measures. Then we used the Adaboost algorithm for the learning phase. All of our work is based on

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Wojtkowski, Maciej, Patrycjusz Stremplewski, Egidijus Auksorius, and Dawid Borycki. "Spatio-Temporal Optical Coherence Imaging – a new tool for in vivo microscopy." Photonics Letters of Poland 11, no. 2 (2019): 44. http://dx.doi.org/10.4302/plp.v11i2.905.

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Optical Coherence Imaging (OCI) including Optical Coherence Tomography (OCT) and Optical Coherence Microscopy (OCM) uses interferometric detection to generate high-resolution volumetric images of the sample at high speeds. Such capabilities are significant for in vivo imaging, including ophthalmology, brain, intravascular imaging, as well as endoscopic examination. Instrumentation and software development allowed to create many clinical instruments. Nevertheless, most of OCI setups scan the incident light laterally. Hence, OCI can be further extended by wide-field illumination and detection. T

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Santhosh, Chella, M. Ravi Kumar, J. Lakshmi Prasanna, I. Ram Kumar, U. Vinay Kumar, and S. Navya Sri. "Face Mask Detection Using LabView." International Journal of Online and Biomedical Engineering (iJOE) 17, no. 06 (2021): 49. http://dx.doi.org/10.3991/ijoe.v17i06.21995.

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<p>Rapid worldwide spread of Corona virus Disease 2019 (COVID 19) has resulted in a global pandemic. In present scenario due to covid-19, the mask has been an important part of our live for our safety as well as for the others safety so there is a need for efficient face mask detection applications in crowded areas like shopping malls, Public transportation etc. To ensure safety of the people in the surroundings. Face Mask Detection using NI LabVIEW. In this project a real-time system is developed to detect whether the person is wearing a mask or not by acquiring a real-time image of him

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Zhang, Hua, Li Jia Wang, Zhen Jie Wang, and Wei Yi Yuan. "View-Invariant Face Detection for Colorful Image." Advanced Materials Research 945-949 (June 2014): 1880–84. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.1880.

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To overcome illumination changes and pose variations, a pose-invariant face detection method is presented. First, an illumination compensation method based on reference white is presented to overcome the lighting variations. The reference white is obtained according to the component Y from YCbCr color space. Then, a mixture face model is constructed by the Cb and Cr from YCbCr color space and H from the HSV color space to extract faces from colorful image. At last, an eyes model is designed to locate eyes in the obtained face images, which can distinguish face from neck and arms ultimately. Th

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Jun, In-Ja, and Kyung-Yong Chung. "Image Enhancement Method Research for Face Detection." Journal of the Korea Contents Association 9, no. 10 (2009): 13–21. http://dx.doi.org/10.5392/jkca.2009.9.10.013.

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Mandhala, V. enkata Naresh, Debnath Bhattacharyya, and Tai-hoon Kim. "Face Detection using Image Morphology – A Review." International Journal of Security and Its Applications 10, no. 4 (2016): 89–94. http://dx.doi.org/10.14257/ijsia.2016.10.4.10.

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Chen, Chichyang, Chiun-Wen Hsu, and Te-Lung Lin. "Image prediction using face detection and triangulation." Pattern Recognition Letters 22, no. 13 (2001): 1347–57. http://dx.doi.org/10.1016/s0167-8655(01)00081-2.

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Di Wen, Hu Han, and Anil K. Jain. "Face Spoof Detection With Image Distortion Analysis." IEEE Transactions on Information Forensics and Security 10, no. 4 (2015): 746–61. http://dx.doi.org/10.1109/tifs.2015.2400395.

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Lee, Joo-shin. "Face region detection algorithm of natural-image." Journal of Korea Institute of Information, Electronics, and Communication Technology 7, no. 1 (2014): 55–60. http://dx.doi.org/10.17661/jkiiect.2014.7.1.055.

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Goswami, Gaurav, Brian M. Powell, Mayank Vatsa, Richa Singh, and Afzel Noore. "FaceDCAPTCHA: Face detection based color image CAPTCHA." Future Generation Computer Systems 31 (February 2014): 59–68. http://dx.doi.org/10.1016/j.future.2012.08.013.

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Kaminski, Jeremy Yrmeyahu, Dotan Knaan, and Adi Shavit. "Single image face orientation and gaze detection." Machine Vision and Applications 21, no. 1 (2008): 85–98. http://dx.doi.org/10.1007/s00138-008-0143-1.

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41

Grudzień, Artur, Marcin Kowalski, and Norbert Pałka. "Thermal Face Verification through Identification." Sensors 21, no. 9 (2021): 3301. http://dx.doi.org/10.3390/s21093301.

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This paper reports on a new approach to face verification in long-wavelength infrared radiation. Two face images were combined into one double image, which was then used as an input for a classification based on neural networks. For testing, we exploited two external and one homemade thermal face databases acquired in various variants. The method is reported to achieve a true acceptance rate of about 83%. We proved that the proposed method outperforms other studied baseline methods by about 20 percentage points. We also analyzed the issue of extending the performance of algorithms. We believe

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Li, Yong Gang, Hai Ming Yin, and Xun Wei Gong. "A Beach Image Detection Method Based on Erotic Image Detection." Applied Mechanics and Materials 278-280 (January 2013): 1282–86. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.1282.

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In the process of erotic image detection, a kind of beach images is often error detected. To solve this problem, a detection model of beach image is designed, which divides the image into two parts to detect: the blue sky in the upper portion and the beach in the lower part. At the same time, a beach naked body detection model is designed to deal with the beach images with naked body, in which OpenCV is used to detect face and naked body. The experimental results show that the proposed method can detect beach image accurately, effectively reduce the error rate of normal image.

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Haidar, Ahmed M. A., Geoffrey O. Asiegbu, Kamarul Hawari, and Faisal A. F. Ibrahim. "Electrical Defect Detection in Thermal Image." Advanced Materials Research 433-440 (January 2012): 3366–70. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.3366.

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Electrical and Electronic objects, which have a temperature of operating condition above absolute zero, emit infrared radiation. This radiation can be measured on the infrared spectral band of the electromagnetic spectrum using thermal imaging. Faults on electrical systems are expensive in terms of plant downtime, damage, loss of production or risk from fire. If the threshold temperature is timely detected, the electrical equipment failures can be avoided. This paper presents a straightforward approach for thermal analysis that examines power loads and large area thermal characteristics. A the

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Sharma, Chandni, Shreya Patel, Abhishek More, Kevin Maisuria, Saheli Patel, and Foram Shah. "Review of Face Detection based on Color Image and Binary Image." International Journal of Computer Applications 134, no. 1 (2016): 22–26. http://dx.doi.org/10.5120/ijca2016907756.

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Muhimmah, Izzati, Nurul Fatikah Muchlis, and Arrie Kurniawardhani. "AUTOMATIC FACIAL REDNESS DETECTION ON FACE SKIN IMAGE." IIUM Engineering Journal 22, no. 1 (2021): 68–77. http://dx.doi.org/10.31436/iiumej.v22i1.1495.

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One facial skin problem is redness. On site examination currently relies on examination through direct observations conducted by doctors and the patient's medical history. However, some patients are reluctant to consult with a doctor because of shame or prohibitive costs. This study attempts to utilize digital image processing algorithms to analyze the patient's facial skin condition automatically, especially redness detection in the face image. The method used for detecting red objects on face skin for this research is Redness method. The output of the Redness method will be optimized by feat

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Voloshyn, Mykola V. "THE IMAGE PREPROCESSING METHOD FOR FACE DETECTION PROBLEMS." KPI Science News, no. 4 (October 15, 2019): 17–23. http://dx.doi.org/10.20535/kpi-sn.2019.4.174381.

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Powell, Brian M., Adam C. Day, Richa Singh, Mayank Vatsa, and Afzel Noore. "Image-based face detection CAPTCHA for improved security." International Journal of Multimedia Intelligence and Security 1, no. 3 (2010): 269. http://dx.doi.org/10.1504/ijmis.2010.037541.

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Yang, Cheng-Yun, and Homer H. Chen. "Efficient Face Detection in the Fisheye Image Domain." IEEE Transactions on Image Processing 30 (2021): 5641–51. http://dx.doi.org/10.1109/tip.2021.3087400.

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al_galib, Shahad laith abd, Asma Abdulelah Abdulrahman, and Fouad Shaker Tahir Al-azawi. "Face Detection for Color Image Based on MATLAB." Journal of Physics: Conference Series 1879, no. 2 (2021): 022129. http://dx.doi.org/10.1088/1742-6596/1879/2/022129.

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Chyad, Haitham Salman, Raniah Ali Mustafa, and Zainab Yasser Mohamed. "Edge Detection for Face Image Using Multiple Filters." International Journal of Engineering Research and Advanced Technology 07, no. 08 (2021): 28–41. http://dx.doi.org/10.31695/ijerat.2021.3736.

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