Search
281 articles for “computer vision”
-
Survey of Intelligent Surveillance System using Image Processing and Deep Learning Techniques
Abstract: Abstract Closed-circuit television systems (CCTV) are becoming more and more pop- ular and are being deployed in many offices, housing estates and most public spaces. Thus, the job of CCTV operators is becoming very challenging as the footage contains a lot of information and gradually becomes cumbersome. Rapid advancement in the field of computer vision could be observed as an important trend in video surveillance and lead to substantial effi- …
Published in Journal of Computer Technology & Applications · Vol. 11, Issue 3, 2020 · pp. 34–64 Read article
-
A Deep Survey on Techniques Used to Recognize Locust Based on CNN
Abstract: The major threat in agriculture is insect pests and crop disease. Outbreaks and upsurges of insects can cause huge loss to crop production. Locusts are crop devouring pests found in many parts of the world. Recognition of locusts in early stage helps to prevent the spread of locusts by taking appropriate counter-measures and biological control methods. Initially, locusts were classified and recognized manually which is time consuming and requires taxonomic …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 1, 2021 · pp. 1–8 Read article
-
The Importance and Misconceptions of Artificial Intelligence in Industry and Academia
Abstract: Artificial Intelligence (AI) has been making remarkable advancements in various industries and academia. AI has been used by businesses to increase productivity, improve efficiency, and make factbased decisions. For example, AI is being used in finance for fraud detection, in healthcare for diagnosis and treatment planning, and in retail for personalized customer experiences. On the other hand, academia has been at the forefront of AI research and development, with a …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 3, 2022 · pp. 40–44 Read article
-
Deep Learning Based Plant Disease Detection
Abstract: Crop diseases are a major threat to food security, but their rapid identification remains difficult in many parts of the world due to the lack of the necessary infrastructure. The combination of increasing global smartphone penetration and recent advances in computer vision made possible by deep learning has paved the way for smartphone-assisted disease diagnosis. Using a public dataset of images of diseased and healthy plant leaves collected under controlled …
Published in Journal Of Network security · Vol. 8, Issue 2, 2020 · pp. 33–42 Read article
-
A Review on CAPTCHAs in Use with Focus on Their Existing Vulnerabilities Concerning Web Security
Abstract: Over last decades or so, CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart)are used to differentiate between humans and bots. In spite of the fact that numerous choices of CAPTCHAs are presented in later a long time but still text-based CAPTCHAs are most predominant among all other choices on the web. CAPTCHA has been broadly utilized over web to guard against assaults from pernicious bots and …
Published in Journal Of Network security · Vol. 9, Issue 1, 2021 · pp. 1–10 Read article
-
Intelligent Automated Guided Vehicle (AGV) System for Optimized Material Handling
Abstract: This project is the development of an Automated Guided Vehicle (AGV) system that has been developed to handle materials in the high-accuracy, reliability, and efficiency in industrial settings. The AGV is a combination of a blend of advanced technologies including sensor fusion, real-time path planning, and AI-based navigation to allow smooth and intelligent operation with minimal human intervention. The vehicle is able to efficiently identify, and evade obstacles by using …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 1–7 Read article
-
An Experimental Analysis on Enhancement of Electric Vehicle Safety using ADAS Technology and Forward Collision Avoidance with an Automatic Braking System
Abstract: The rapid expansion of the automobile sector in developing nations has intensified road safety concerns, particularly in congested urban environments where human error accounts for approximately 90% of all accidents. This paper presents and experimentally validates an integrated Advanced Driver Assistance System (ADAS) for electric vehicles comprising three complementary safety modules: a Forward Collision Avoidance System (FCAS) employing an HC-SR04 ultrasonic sensor interfaced with an Arduino Uno R3 to detect …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 2, 2026 · pp. 20–30 Read article
-
Deep Learning for Traffic Sign Recognition in Autonomous Vehicles: Challenges, Trends and Future Directions
Abstract: Traffic Sign Recognition (TSR) serves as a fundamental task in the domain of autonomous vehicles (AVs), enabling systems to detect, classify, and respond to road signs with the level of accuracy and speed required for safe navigation. As AV technology continues to evolve, the role of intelligent TSR systems has become increasingly vital. Traditional computer vision techniques, while foundational, often fall short under challenging real-world conditions such as poor lighting, …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 2, 2026 · pp. 1–7 Read article
-
A Novel Approach to Reduce Image Retrieval Problem Using Gabor Transform, Wavelet Transform and Euclidean Distance Measure
Abstract: In the processing of image, pattern recognition and computer vision, the image retrieval is a most famous research area. Our paper presents a new method in CBIR through merging the low level feature i.e. texture, color and shape features. At first, we transform the color space from RGB model to HSV model, and then extract color histogram to form color feature vector. CBIR is the process where search of image …
Published in E-Commerce for Future & Trends · Vol. 3, Issue 1, 2016 · pp. 10–15 Read article
-
A Robust Face Recognition Model based on Convolutional Neural Networks
Abstract: From the past several years, face recognition is one of the challenging issues in computer vision, due to three main technical problems in it. 1) Expression problem: in which same person shows more than one expression. 2) Illumination problem: in which face images of the person are strongly corrupted by lightning and 3) poses problem: in which large portion of the face becomes invisible due to occlusion. To this end …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 1, 2018 · pp. 1–11 Read article
-
Multiclass Content-based Visual Information Retrieval using Multi Layer Perceptron and Convolution Neural Network: A Comparative Study
Abstract: Content-based visual information extraction is an area, which utilizes the computer vision methods for searching and indexing the images in image library more competently than manual annotations. Due to the exponentially increase in image database volume, there is a demand of efficient retrieval system. Deep learning-based machine vision systems have the ability to handle large amount of data efficiently than ordinary machine vision systems. This paper proposed a content-based image …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 1, 2020 · pp. 1–9 Read article
-
A Review on Crowd Analysis Techniques
Abstract: AbstractNowadays Crowd analysis is an active open research problem in Computer Vision field. Its various applications like Crowd management, Public space design, Virtual environments, Visual surveillance, and intelligent environments attract researchers. Today security is major concerned, and any abnormal activity can automatically be detected by crowd analysis, so this research topic has got good attention of different researchers. Abnormal activity detection in the crowd is a very challenging task because …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 2, 2019 · pp. 119–126 Read article
-
Malaria Parasite Detection in Thin Blood Smear Images Using Deep Learning
Abstract: Algorithms in deep neural networks are being used to show the presence of malaria and to estimate the depth of infection by automatically counting individual uninfected and infected RBCs in images of thin blood smears. During the training period, the relationship was tried on a set of 13600 images from several thin blood spreads and experiment was conducted. My dataset is divided into 80% for training and 20% for testing. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 1, 2020 · pp. 28–32 Read article
-
Extracting Alphabets and Numbers from License Plate using Mean Value
Abstract: Segmentation plays a significant role in computer vision and its related applications of image processing. Segmentation is actually a process of partitioning a digital image into multiple segments (sets of pixels) to simplify and/or change the representation of an image into more meaningful and easier to analyze. This paper presents a method of license plate extraction using segmentation method and mean value of the images. We extracted the numbers and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 3, 2014 · pp. 1–8 Read article
-
A Survey on Face Recognition Techniques and Its Applications
Abstract: Face recognition has been a fast growing, and interesting area in real time applications. Automatic face recognition has shown great achievement for high-quality images under embarrassed conditions; for video-based recognition it is hard to achieve similar levels of performance. Human face detection and tracking of moving objects in the video are important tasks of the computer vision. Human and object frames are separated by implementing a face detection algorithm for …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 3, 2014 · pp. 16–21 Read article
-
Efficient Object Detection Based on Local Invariant Features
Abstract: Object detection is an important task in image processing and computer vision. Binary Robust Invariant Scalable Keypoint (BRISK) local features are extracted from the object. These features are invariant to image scale, translation, rotation, illumination and partial occlusion. Object detection process begins by matching individual features of the user queried object to a database of features with different objects which are saved in advance. Cite this Article:Anand Rathod, Manoj Bagale, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 2, 2015 · pp. 1–3 Read article
-
A Comparative Study on Different Edge Detection Techniques after Applying Noise Removal Techniques to An Image
Abstract: In digital image processing and computer vision, image segmentation plays an important part. image segmentation refers to the sub division of image into different parts on the basis of different factors like edges, region, etc. edge detection is the most important factor of object recognition in an image. but unwanted signals like noise in an image can affect and degrade the edge detection process in image segmentation. this paper aims …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 2, 2015 · pp. 33–40 Read article
-
Detect the Edges of Hygienic Images and De-Noised Images Using Meta Heuristic and F-Ratio
Abstract: AbstractEdge detection is one of the important parts of image processing. It is essentially involved in the pre-processing stage of image analysis and computer vision. It generally detects the contour of an image and thus provides important details about an image. So, it reduces the content to process for the high-level processing tasks like object recognition and image segmentation. The most important step in the edge detection, on which the …
Published in Journal of Advances in Shell Programming · Vol. 4, Issue 2, 2017 · pp. 19–25 Read article
-
Facial Recognition Based Attendance System
Abstract: In today’s fast paced world, for an organization with around 500 employees, a manual attendance system is highly inefficient and time consuming. Traditional methods of automatic attendance systems like fingerprint, RFID or iris scans are easy to bypass, as the biometric features, such systems take into consideration are far less than facial features. Our facial recognition system is used to detect a person’s face and then compare it with the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 2, 2016 · pp. 43–49 Read article
-
Human Motion Recognition Using Optical Flow Based Particle Filtering
Abstract: ABSTRACTHuman motion recognition has been a significant topic in computer vision due to its numerous applications such as video surveillance, human machine interaction and video retrieval. One core difficulty behind these applications is mechanically identifying low-level actions and high-level activities of concern. This paper presents a technique of automatically identifying the motion accomplished by humans. The speeded up robust features (Optical flow with kinetic energy algorithm) are made use of, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 1, 2018 · pp. 1–9 Read article