scholarly journals Estimation of Traffic Occupancy using Image Segmentation

2021 ◽  
Vol 11 (4) ◽  
pp. 7291-7295
Author(s):  
M. U. Farooq ◽  
A. Ahmed ◽  
S. M. Khan ◽  
M. B. Nawaz
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Road Traffic ◽  
Low Cost ◽  
Traffic Monitoring ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Percentage Difference ◽  
Novel Approach ◽  
Removal Technique

Increased traffic flow results in high road occupancy. Traffic road occupancy is often used as a parameter for the prediction of traffic conditions by traffic engineers. Although traffic monitoring systems are based on a large number of technologies, challenges are still present. Most of the methods work efficiently for free-flow traffic but not in heavy congestion. Image processing techniques are more effective than other methods, as they are based on loop sensors and detectors to monitor road traffic. A huge number of image frames are processed in image processing hence there is a need for a more efficient and low-cost image processing technique for accurate vehicle detection. In this paper, a novel approach is adopted to calculate road occupancy. The proposed framework has robust performance under road conjunction and diverse environmental conditions. A combination of image segmentation threshold technique and shadow removal technique is used. The study comprised of segmenting 1056 images extracted from recorded videos. The obtained results by image segmentation were compared with traffic road occupancy calculated manually using Autocad. A final percentage difference of 8.7 was observed.

Review on 2D and 3D MRI Image Segmentation Techniques

2019 ◽  
Vol 15 (2) ◽  
pp. 150-160 ◽  
Author(s):  
S. Shirly ◽  
K. Ramesh
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Medical Image ◽  
Medical Diagnostics ◽  
Processing Technique ◽  
Image Features ◽  
Medical Image Segmentation ◽  
Image Processing Technique ◽  
Edge Based ◽  
Mri Image

Background: Magnetic Resonance Imaging is most widely used for early diagnosis of abnormalities in human organs. Due to the technical advancement in digital image processing, automatic computer aided medical image segmentation has been widely used in medical diagnostics. </P><P> Discussion: Image segmentation is an image processing technique which is used for extracting image features, searching and mining the medical image records for better and accurate medical diagnostics. Commonly used segmentation techniques are threshold based image segmentation, clustering based image segmentation, edge based image segmentation, region based image segmentation, atlas based image segmentation, and artificial neural network based image segmentation. Conclusion: This survey aims at providing an insight about different 2-Dimensional and 3- Dimensional MRI image segmentation techniques and to facilitate better understanding to the people who are new in this field. This comparative study summarizes the benefits and limitations of various segmentation techniques.

scholarly journals Beef Quality Identification Using Thresholding Method and Decision Tree Classification Based on Android Smartphone

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Kusworo Adi ◽  
Sri Pujiyanto ◽  
Oky Dwi Nurhayati ◽  
Adi Pamungkas
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Decision Tree ◽  
Processing Technique ◽  
Automated System ◽  
Image Processing Technique ◽  
Marbling Score ◽  
Beef Quality ◽  
Thresholding Method ◽  
Acquisition Processes

Beef is one of the animal food products that have high nutrition because it contains carbohydrates, proteins, fats, vitamins, and minerals. Therefore, the quality of beef should be maintained so that consumers get good beef quality. Determination of beef quality is commonly conducted visually by comparing the actual beef and reference pictures of each beef class. This process presents weaknesses, as it is subjective in nature and takes a considerable amount of time. Therefore, an automated system based on image processing that is capable of determining beef quality is required. This research aims to develop an image segmentation method by processing digital images. The system designed consists of image acquisition processes with varied distance, resolution, and angle. Image segmentation is done to separate the images of fat and meat using the Otsu thresholding method. Classification was carried out using the decision tree algorithm and the best accuracies were obtained at 90% for training and 84% for testing. Once developed, this system is then embedded into the android programming. Results show that the image processing technique is capable of proper marbling score identification.

A Novel Approach of Controlling Stoppage of Drip Infusion Using Image Processing on Raspberry PI Platform

2021 ◽  
Vol 58 (S) ◽  
pp. 65-72
Author(s):  
Hartono Pranjoto ◽  
Lanny Agustine ◽  
Diana Lestariningsih ◽  
Yesiana Dwi Wahyu Werdani ◽  
Widya Andyardja ◽  
...  
Keyword(s):  
Image Processing ◽  
Digital Camera ◽  
Detection Algorithm ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Novel Approach ◽  
Pinch Valve ◽  
Canny Edge ◽  
Infusion Fluid

Intravenous drip diffusion is a common practice to treat patients in hospitals. During treatment, nurses must check the condition of the infusion bag frequently before running out of fluid. This research proposes a novel method of checking the infusion bag using an image processing technique on a compact Raspberry PI platform. The infusion monitoring system proposed here is based solely on capturing the image of the infusion bag and the accompanying bag/ tube. When the infusion fluid enters the patient, the surface of the liquid will decrease, and at the end will reach the bottom of the infusion bag. When the image of the fluid surface touches the bottom of the infusion bag, a mechanism will trigger a relay, and then activate a pinch valve to stop the flow of the infusion fluid before it runs out. The entire system incorporates a digital camera and Raspberry as the image processor. The surface of the liquid is determined using the Canny Edge Detection algorithm, and its relative position in the tube is determined using the Hough Line Transform. The raw picture of the infusion bag and the processed image are then sent via a wireless network to become part of a larger system and can be monitored via a simple smartphone equipped with the proper application, thus becoming an Internet of Things (IoT). With this approach, nurses can carry on other tasks in caring for the patients while this system substitutes some work on checking the infusion fluid.

IMAGE SEGMENTATION TECHNIQUES FOR RED BLOOD CELL : ON OVERVIEW

2015 ◽  
Vol 77 (6) ◽  
Author(s):  
Laghouiter Oussama ◽  
M. Mahadi Abdul Jamil ◽  
Wan Mahani Hafiza Bt. Wan Mahmud
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Blood Cell ◽  
Blood Cells ◽  
Medical Image Analysis ◽  
White Blood Cells ◽  
Critical Factor ◽  
Processing Technique ◽  
Image Processing Technique ◽  
The Common

Image processing technique applies in different domains, such as medical, remote sensing and security. This techniques Aims to get a simple image called -image processed- should retain maximum useful information. The sensitive step in image processing is segmentation of image. Segmentation is first stage in medical image analysis seeded to two categories supervised and unsupervised technique. Accuracy of this stage affects the whole system performance. This paper present some methods applied for blood cell image segmentation and compares previous studies of overlapping cell division method. The common goal about this area is accuracy of counting the number of red blood cells (RBC) or white blood cells (WBC), which decrease with effect of some diseases such as anemia and leukemia. And makes it a critical factor in patient treatments.

scholarly journals SMT Component Inspection in PCBA’s using Image Processing Techniques

2019 ◽  
Vol 8 (12) ◽  
pp. 541-547
Keyword(s):  
Image Processing ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Low Cost ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Reference Image ◽  
Small Scale ◽  
Contour Analysis ◽  
Automated Optical Inspection

In the present evolving technology, an Automated Optical Inspection is a solution for identifying the various types of defects occurring in assembled PCB with SMT components. As these high-end machines are expensive, moreover the small scale industries can’t afford such a huge investment, in this paper a low cost image processing technique where a good known reference image is compared with the acquired image is being tried. This work provides an automated approach for identifying few of the defects related to the SMT components found in the assembled PCB, using three different techniques namely Contour Analysis, Optical Character Recognition and Pixel Subtraction for identifying shifted components, value of the components and missing components respectively in LabVIEW platform. The time taken for identifying the various defects through different techniques are calculated and tabulated. Using these techniques the number of errors can be decreased in turn the end performance can also be enhanced with the increased production yield.

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