farah AL-KHALIDI - Academia.edu (original) (raw)
Papers by farah AL-KHALIDI
Evaluation Software and IT Integration for IoT-based Healthcare Radio Frequency Identification Network Planning
Intelligent application for COVID-19 diagnosis using CT scan
AIP Conference Proceedings, Dec 31, 2022
Mobile remote surveillance system for home security issues: Review
INTERNATIONAL CONFERENCE ON SCIENTIFIC RESEARCH & INNOVATION (ICSRI 2022)
International Journal of Surgery, 2016
prospectively collected over a 30-month period. Multivariate analysis investigated effects of bes... more prospectively collected over a 30-month period. Multivariate analysis investigated effects of best practice achievement, age and ISS on Glasgow Outcome Score (GOS) and 30 day mortality in younger and elderly patient groups. Results: In younger patients (n ¼ 1393), four of the 10 best practice indicators analysed showed independent significance in improving GOS (p < 0.05 for all), and one in independently reducing mortality (p < 0.05). In elderly patients (n ¼ 896), none of the trauma best practice indicator significantly improved either outcome measure. ISS and age were independent, additive factors for GOS and mortality (p < 0.001). Conclusions: With outcomes significantly worse in older patients, the lack of improvement with "best practice" indicates an important area for wider study, and may be due either to an underestimation of their injury severity, or best practice indicators inappropriate for this group.
Mobile remote surveillance system for home security issues: Review
INTERNATIONAL CONFERENCE ON SCIENTIFIC RESEARCH & INNOVATION (ICSRI 2022)
International Journal of Computing and Digital Systems
Every citizen wants to eliminate any potential threat to themselves or their belongings. A proper... more Every citizen wants to eliminate any potential threat to themselves or their belongings. A proper and modern surveillance system is necessary given the enormous increase in the security needs of both persons and organizations. Remote surveillance is one of the major issues which attracted the attention of researchers recently. Surveillance cameras, commonly known as closed-circuit television (CCTV) have grown rapidly in popularity over the last few decades. Nowadays, video surveillance is quite essential. It greatly aids in reducing crime rates and can be used to keep track of the condition of buildings. In this paper, a remote surveillance system using the Convolutional Neural Networks (CNN) model was proposed. This system consists of a camera that takes more than one image of the object that passes in front of it and sends these images to the mobile phone of the intended person (the owner of the place). Images taken by the security camera may be analyzed using the CNN model depending on the region of interest for detection. The system will be delivering an alarm to the user depending on intelligent detection depending on a deep learning approach that can improve a smart home automation structure by detection people. The results of the experiments demonstrate a high degree of accuracy in detecting human beings , the accuracy of the system reached 100% in an ideal time.
A review of covid-19 detection and diagnosis methods based on deep learning
Nucleation and Atmospheric Aerosols, 2022
International Journal of Interactive Mobile Technologies (iJIM)
The main target of the work in this paper is to detect the gender and oldness of a person with an... more The main target of the work in this paper is to detect the gender and oldness of a person with an accurate decision and efficient time based on the number of facial outward attributes extracted using Linear-Discriminate Analysis to classify a person within a certain category according to his(her) gender and age. This work was deal with color facial images via the Iterative Dichotomiser3 algorithm as a classifier to detect the oldness of a person after gender detected. This paper used the Face-Gesture-Recognition-Research-Network aging dataset. All facial images in the dataset were categorizing into binary categories using k-means. This is followed by the process of dividing all samples according to age classes that belonging to each specific sex category. Thus, this division process enabled us to reach a quick and accurate decision. The results showed that the accuracy of the proposal was 90.93%, and F-measure was 89.4.
Monitoring respiration rate, i.e. the rate air is inhaled and exhaled is an important indicator o... more Monitoring respiration rate, i.e. the rate air is inhaled and exhaled is an important indicator of an individual’s health. Respiration rate is generally measured using sensors attached to the patient's body. These contact based methods have a number of limitations, for example the attached sensor can cause discomfort to the patients. A novel, automated, non-contact based method of respiration monitoring, based on thermal imaging of the skin surface centered on the tip of the nose for the nose breathing as well as the mouth region for the mouth breathing. These methods are developed as well as the Image processing techniques were used to enhance the thermal images, remove unwanted noise and segmented the ROI. In this study the shape and size of the region of interest (ROI) are investigated. The ROI represents the facial affected area most affected by exhaled air temperature changes. This area is the tip of the nose and the upper lip for the nose breathing and the mouth area for ...
Tracking human face features in thermal images for respiration monitoring
Respiration rate is one of the main indicators of an individual's health and therefore it req... more Respiration rate is one of the main indicators of an individual's health and therefore it requires accurate quantification. Its value can be used to predict life threatening conditions such as the child death syndrome and heart attacks. The current respiration rate monitoring methods are contact based, i.e. a sensing device needs to be attached to the person's body. Physically constraining infants and young children by a sensing device can be stressful to the individuals which in turn affects their respiration rate. Therefore, measuring respiration rate in a non-contact manner (i.e. without attaching the sensing device to the subject) has distinct benefits. Currently there is not any non-contact respiration rate monitoring available for use in medical field.The aim of this study was to investigate thermal imaging as a means for non-contact respiration rate monitoring. Thermal imaging is safe and easy to deploy. Twenty children were enrolled for the study at Sheffield Childre...
Extraction the Facial Features of the Human Face: Extracting the face and the facial features(eyes, nose and mouth ) using Matlab Software
<jats:p>This project presents a new approach for automatically tracking the human face as w... more <jats:p>This project presents a new approach for automatically tracking the human face as well as facial features (nose, mouth, eyes)in a clear way. This technique became required in various future visual communication applications, such as teleconferencing, Facial recognition systems, Biometrics and Human computer interface etc. The principle behind detecting the face feature is used to measure the respiration rate in the future as the nose represents the important region in the human face for breathing. Human face detection as elliptical area was investigated then image processing techniques were used to extract human face as elliptical area from the rest of image. Several techniques were applied to detect the nose inside the elliptical area as rectangle region and then the mouth and eyes regions were extracted inside the elliptical face area. A skin-color segmentation with image processing techniques played an important role in detecting the human face as elliptic area and then several techniques were used such as enhancement, thresholding, Morphological, edge detections as well as binarization techniques to achieve the aims of the suggested methods. Nose detection as a rectangle region was also investigated by looking for the longest vertical line in the elliptical area. The nose was detected and extracted as rectangle region. Detecting the mouth was achieved by looking for the longest horizontal line under the tip of the nose then thresholding this region to detect the lips of the mouth; by extracting the points of the lips corners we extracted the mouth as elliptical region. Finally, the eye regions were tracked in the upper part of ellipse above the tip of the nose and detected as rectangular regions. Further work is in progress to enhance these techniques to take place in real time images as well as apply them in the medical field.</jats:p>
Challenges in thermal imaging based respiration rate monitoring
Respiration rate is an important physiological measure. Current respiration rate monitoring metho... more Respiration rate is an important physiological measure. Current respiration rate monitoring methods are contact based, i.e. the sensing device is attached to the subject's body. These methods create discomfort and in some cases affect the value of the respiration rate.
Respiratory rate is a vital physiological measurement used in the immediate assessment of unwell ... more Respiratory rate is a vital physiological measurement used in the immediate assessment of unwell children. Convenient electronic devices exist for measurement of pulse, blood pressure, oxygen saturation and temperature. Although devices which measure respiratory rate exist, none has entered everyday clinical practice. An accurate device which has no physical contact with the child is important to ensure readings are not affected by distress. A thermal imaging camera to monitor respiratory rate in children was evaluated. Facial thermal images of 20 children (age: median=6.5 years, range 6 months-17 years) were included in the study. Recordings were performed while the children slept comfortably on a bed for a duration of two minutes. Values obtained using the thermal imaging camera were compared with those obtained from standard methods: nasal thermistor, respiratory impedance plethysmography and transcutaneous CO2. Median respiratory rate measurements per minute were 21.0 (range 15....
Extract the Breast Cancer in Mammogram Images
Image processing techniques play a significant role in many areas in life, especially in medical ... more Image processing techniques play a significant role in many areas in life, especially in medical images, where they play a prominent role in diagnosing many diseases such as detection of the brain tumor, breast cancer, kidney cancer, and the fractions. Breast cancer is a common disease, regardless of the type of this disease, whether it is benign or malignant, it is very dangerous and early detection may reduce the risk of the disease spreading in the body leading to death. This work presents an approach to detect breast cancer based on image processing algorithms, including image preprocessing, enhancement, segmentation, Morphological operations, and feature extraction to detect and extract the breast cancer region.
Eyes Detection in the Human Face
Eye detection is important for some applications such as tracking system, video conferencing, fac... more Eye detection is important for some applications such as tracking system, video conferencing, face detection and recognition systems. In this work, threshold technique was being used considering HSV color information generated from the true color image, Hue and value of saturation will be used to get an object of the input image and then use those results at the stage of facial properties detection such as the eyes. Geometrical positions are used on portions of the face to determine the upper part for eyes position. The detection method stands for considering eye features from variance threshold and the distances between each eye. By testing 40 true color images of face images and the various circumstances of light or dark, has proved a successful way to detect the eyes of the human face.
Number 4
Quality and execution time are two important factors for evaluation of edge detection algorithms.... more Quality and execution time are two important factors for evaluation of edge detection algorithms. In these algorithms, there is a trade-off between quality and execution time. Some algorithms only concentrate on quality and some of them are fast and low quality. Efficient methods try to achieve high quality in a low time. This research concentrates on improvement of gradient based edge detection that is fast method and appropriate for real-time processing. The proposed algorithm reduces execution time by removing many pixels from computations. It calculates gradient and angle class of remaining pixels in a very efficient way so that it reinforces quality and locality of edges. The results of this algorithm indicated improvement of performance in comparison to Canny and LOG algorithms.
Facial tracking method for noncontact respiration rate monitoring
2010 7th International Symposium on Communication Systems, Networks & Digital Signal Processing (CSNDSP 2010), 2010
A non-contact method of monitoring respiration rate is developed. The approach involved tracking ... more A non-contact method of monitoring respiration rate is developed. The approach involved tracking a facial region of interest (ROI) associated with respiration in thermal images. Image processing techniques were used to enhance the recorded thermal images and to remove unwanted noise. The skin surface area centered on the tip of the nose was specified by a circle that covered the
Nose Detection In The Human Face
المجلة العراقية لتكنولوجيا المعلومات, 2017
American Journal of Engineering and Applied Sciences, 2011
Problem statement: An important indicator of an individual's health is respiration rate. It is th... more Problem statement: An important indicator of an individual's health is respiration rate. It is the average number of times air is inhaled and exhaled per minute. Existing respiration monitoring methods require an instrument to be attached to the patient's body during the recording. This is a discomfort to the patient and the instrument can be dislodged from its position. Approach: In this study a novel noncontact, thermal imaging based respiration rate measurement method is developed and evaluated. Facial thermal videos of 16 children (age: Median = 6.5 years, minimum = 6 months, maximum = 17 years) were processed in the study. The recordings were carried out while the children rested comfortably on a bed. The children's respiration rates were also simultaneously measured using a number of conventional contact based methods. Results: This allowed comparisons with the thermal imaging method to be carried out. The image capture rate was 50 frames per second and the duration of a thermal video recording was 2 min per child. The thermal images were filtered and segmented to identify the nasal region. An algorithm was developed to automatically track the identified nasal area. This region was partitioned into eight equal concentric segments. The pixel values within each segment were averaged to produce a single thermal feature for that segment of the image. A respiration signal was obtained by plotting each segment's feature against time. Conclusion: Respiration rate values were automatically calculated by determining the number of oscillations in the respiration signals per minute. A close correlation (coefficient = 0.994) was observed between the respiration rates measured using the thermal imaging method and those obtained using the most effective conventional contact based respiration method.
Evaluation Software and IT Integration for IoT-based Healthcare Radio Frequency Identification Network Planning
Intelligent application for COVID-19 diagnosis using CT scan
AIP Conference Proceedings, Dec 31, 2022
Mobile remote surveillance system for home security issues: Review
INTERNATIONAL CONFERENCE ON SCIENTIFIC RESEARCH & INNOVATION (ICSRI 2022)
International Journal of Surgery, 2016
prospectively collected over a 30-month period. Multivariate analysis investigated effects of bes... more prospectively collected over a 30-month period. Multivariate analysis investigated effects of best practice achievement, age and ISS on Glasgow Outcome Score (GOS) and 30 day mortality in younger and elderly patient groups. Results: In younger patients (n ¼ 1393), four of the 10 best practice indicators analysed showed independent significance in improving GOS (p < 0.05 for all), and one in independently reducing mortality (p < 0.05). In elderly patients (n ¼ 896), none of the trauma best practice indicator significantly improved either outcome measure. ISS and age were independent, additive factors for GOS and mortality (p < 0.001). Conclusions: With outcomes significantly worse in older patients, the lack of improvement with "best practice" indicates an important area for wider study, and may be due either to an underestimation of their injury severity, or best practice indicators inappropriate for this group.
Mobile remote surveillance system for home security issues: Review
INTERNATIONAL CONFERENCE ON SCIENTIFIC RESEARCH & INNOVATION (ICSRI 2022)
International Journal of Computing and Digital Systems
Every citizen wants to eliminate any potential threat to themselves or their belongings. A proper... more Every citizen wants to eliminate any potential threat to themselves or their belongings. A proper and modern surveillance system is necessary given the enormous increase in the security needs of both persons and organizations. Remote surveillance is one of the major issues which attracted the attention of researchers recently. Surveillance cameras, commonly known as closed-circuit television (CCTV) have grown rapidly in popularity over the last few decades. Nowadays, video surveillance is quite essential. It greatly aids in reducing crime rates and can be used to keep track of the condition of buildings. In this paper, a remote surveillance system using the Convolutional Neural Networks (CNN) model was proposed. This system consists of a camera that takes more than one image of the object that passes in front of it and sends these images to the mobile phone of the intended person (the owner of the place). Images taken by the security camera may be analyzed using the CNN model depending on the region of interest for detection. The system will be delivering an alarm to the user depending on intelligent detection depending on a deep learning approach that can improve a smart home automation structure by detection people. The results of the experiments demonstrate a high degree of accuracy in detecting human beings , the accuracy of the system reached 100% in an ideal time.
A review of covid-19 detection and diagnosis methods based on deep learning
Nucleation and Atmospheric Aerosols, 2022
International Journal of Interactive Mobile Technologies (iJIM)
The main target of the work in this paper is to detect the gender and oldness of a person with an... more The main target of the work in this paper is to detect the gender and oldness of a person with an accurate decision and efficient time based on the number of facial outward attributes extracted using Linear-Discriminate Analysis to classify a person within a certain category according to his(her) gender and age. This work was deal with color facial images via the Iterative Dichotomiser3 algorithm as a classifier to detect the oldness of a person after gender detected. This paper used the Face-Gesture-Recognition-Research-Network aging dataset. All facial images in the dataset were categorizing into binary categories using k-means. This is followed by the process of dividing all samples according to age classes that belonging to each specific sex category. Thus, this division process enabled us to reach a quick and accurate decision. The results showed that the accuracy of the proposal was 90.93%, and F-measure was 89.4.
Monitoring respiration rate, i.e. the rate air is inhaled and exhaled is an important indicator o... more Monitoring respiration rate, i.e. the rate air is inhaled and exhaled is an important indicator of an individual’s health. Respiration rate is generally measured using sensors attached to the patient's body. These contact based methods have a number of limitations, for example the attached sensor can cause discomfort to the patients. A novel, automated, non-contact based method of respiration monitoring, based on thermal imaging of the skin surface centered on the tip of the nose for the nose breathing as well as the mouth region for the mouth breathing. These methods are developed as well as the Image processing techniques were used to enhance the thermal images, remove unwanted noise and segmented the ROI. In this study the shape and size of the region of interest (ROI) are investigated. The ROI represents the facial affected area most affected by exhaled air temperature changes. This area is the tip of the nose and the upper lip for the nose breathing and the mouth area for ...
Tracking human face features in thermal images for respiration monitoring
Respiration rate is one of the main indicators of an individual's health and therefore it req... more Respiration rate is one of the main indicators of an individual's health and therefore it requires accurate quantification. Its value can be used to predict life threatening conditions such as the child death syndrome and heart attacks. The current respiration rate monitoring methods are contact based, i.e. a sensing device needs to be attached to the person's body. Physically constraining infants and young children by a sensing device can be stressful to the individuals which in turn affects their respiration rate. Therefore, measuring respiration rate in a non-contact manner (i.e. without attaching the sensing device to the subject) has distinct benefits. Currently there is not any non-contact respiration rate monitoring available for use in medical field.The aim of this study was to investigate thermal imaging as a means for non-contact respiration rate monitoring. Thermal imaging is safe and easy to deploy. Twenty children were enrolled for the study at Sheffield Childre...
Extraction the Facial Features of the Human Face: Extracting the face and the facial features(eyes, nose and mouth ) using Matlab Software
<jats:p>This project presents a new approach for automatically tracking the human face as w... more <jats:p>This project presents a new approach for automatically tracking the human face as well as facial features (nose, mouth, eyes)in a clear way. This technique became required in various future visual communication applications, such as teleconferencing, Facial recognition systems, Biometrics and Human computer interface etc. The principle behind detecting the face feature is used to measure the respiration rate in the future as the nose represents the important region in the human face for breathing. Human face detection as elliptical area was investigated then image processing techniques were used to extract human face as elliptical area from the rest of image. Several techniques were applied to detect the nose inside the elliptical area as rectangle region and then the mouth and eyes regions were extracted inside the elliptical face area. A skin-color segmentation with image processing techniques played an important role in detecting the human face as elliptic area and then several techniques were used such as enhancement, thresholding, Morphological, edge detections as well as binarization techniques to achieve the aims of the suggested methods. Nose detection as a rectangle region was also investigated by looking for the longest vertical line in the elliptical area. The nose was detected and extracted as rectangle region. Detecting the mouth was achieved by looking for the longest horizontal line under the tip of the nose then thresholding this region to detect the lips of the mouth; by extracting the points of the lips corners we extracted the mouth as elliptical region. Finally, the eye regions were tracked in the upper part of ellipse above the tip of the nose and detected as rectangular regions. Further work is in progress to enhance these techniques to take place in real time images as well as apply them in the medical field.</jats:p>
Challenges in thermal imaging based respiration rate monitoring
Respiration rate is an important physiological measure. Current respiration rate monitoring metho... more Respiration rate is an important physiological measure. Current respiration rate monitoring methods are contact based, i.e. the sensing device is attached to the subject's body. These methods create discomfort and in some cases affect the value of the respiration rate.
Respiratory rate is a vital physiological measurement used in the immediate assessment of unwell ... more Respiratory rate is a vital physiological measurement used in the immediate assessment of unwell children. Convenient electronic devices exist for measurement of pulse, blood pressure, oxygen saturation and temperature. Although devices which measure respiratory rate exist, none has entered everyday clinical practice. An accurate device which has no physical contact with the child is important to ensure readings are not affected by distress. A thermal imaging camera to monitor respiratory rate in children was evaluated. Facial thermal images of 20 children (age: median=6.5 years, range 6 months-17 years) were included in the study. Recordings were performed while the children slept comfortably on a bed for a duration of two minutes. Values obtained using the thermal imaging camera were compared with those obtained from standard methods: nasal thermistor, respiratory impedance plethysmography and transcutaneous CO2. Median respiratory rate measurements per minute were 21.0 (range 15....
Extract the Breast Cancer in Mammogram Images
Image processing techniques play a significant role in many areas in life, especially in medical ... more Image processing techniques play a significant role in many areas in life, especially in medical images, where they play a prominent role in diagnosing many diseases such as detection of the brain tumor, breast cancer, kidney cancer, and the fractions. Breast cancer is a common disease, regardless of the type of this disease, whether it is benign or malignant, it is very dangerous and early detection may reduce the risk of the disease spreading in the body leading to death. This work presents an approach to detect breast cancer based on image processing algorithms, including image preprocessing, enhancement, segmentation, Morphological operations, and feature extraction to detect and extract the breast cancer region.
Eyes Detection in the Human Face
Eye detection is important for some applications such as tracking system, video conferencing, fac... more Eye detection is important for some applications such as tracking system, video conferencing, face detection and recognition systems. In this work, threshold technique was being used considering HSV color information generated from the true color image, Hue and value of saturation will be used to get an object of the input image and then use those results at the stage of facial properties detection such as the eyes. Geometrical positions are used on portions of the face to determine the upper part for eyes position. The detection method stands for considering eye features from variance threshold and the distances between each eye. By testing 40 true color images of face images and the various circumstances of light or dark, has proved a successful way to detect the eyes of the human face.
Number 4
Quality and execution time are two important factors for evaluation of edge detection algorithms.... more Quality and execution time are two important factors for evaluation of edge detection algorithms. In these algorithms, there is a trade-off between quality and execution time. Some algorithms only concentrate on quality and some of them are fast and low quality. Efficient methods try to achieve high quality in a low time. This research concentrates on improvement of gradient based edge detection that is fast method and appropriate for real-time processing. The proposed algorithm reduces execution time by removing many pixels from computations. It calculates gradient and angle class of remaining pixels in a very efficient way so that it reinforces quality and locality of edges. The results of this algorithm indicated improvement of performance in comparison to Canny and LOG algorithms.
Facial tracking method for noncontact respiration rate monitoring
2010 7th International Symposium on Communication Systems, Networks & Digital Signal Processing (CSNDSP 2010), 2010
A non-contact method of monitoring respiration rate is developed. The approach involved tracking ... more A non-contact method of monitoring respiration rate is developed. The approach involved tracking a facial region of interest (ROI) associated with respiration in thermal images. Image processing techniques were used to enhance the recorded thermal images and to remove unwanted noise. The skin surface area centered on the tip of the nose was specified by a circle that covered the
Nose Detection In The Human Face
المجلة العراقية لتكنولوجيا المعلومات, 2017
American Journal of Engineering and Applied Sciences, 2011
Problem statement: An important indicator of an individual's health is respiration rate. It is th... more Problem statement: An important indicator of an individual's health is respiration rate. It is the average number of times air is inhaled and exhaled per minute. Existing respiration monitoring methods require an instrument to be attached to the patient's body during the recording. This is a discomfort to the patient and the instrument can be dislodged from its position. Approach: In this study a novel noncontact, thermal imaging based respiration rate measurement method is developed and evaluated. Facial thermal videos of 16 children (age: Median = 6.5 years, minimum = 6 months, maximum = 17 years) were processed in the study. The recordings were carried out while the children rested comfortably on a bed. The children's respiration rates were also simultaneously measured using a number of conventional contact based methods. Results: This allowed comparisons with the thermal imaging method to be carried out. The image capture rate was 50 frames per second and the duration of a thermal video recording was 2 min per child. The thermal images were filtered and segmented to identify the nasal region. An algorithm was developed to automatically track the identified nasal area. This region was partitioned into eight equal concentric segments. The pixel values within each segment were averaged to produce a single thermal feature for that segment of the image. A respiration signal was obtained by plotting each segment's feature against time. Conclusion: Respiration rate values were automatically calculated by determining the number of oscillations in the respiration signals per minute. A close correlation (coefficient = 0.994) was observed between the respiration rates measured using the thermal imaging method and those obtained using the most effective conventional contact based respiration method.