Towards a fully automated car parking system

Mahmood, Zahid; Haneef, Ossama; Muhammad, Nazeer; Khattak, Shahid

doi:10.1049/iet-its.2018.5021

Cited by 41 publications

(15 citation statements)

References 34 publications

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“…The current intelligent parking system has excellent advantages in terms of rapid vehicle approach, parking space guidance and fast payment. However, the function of reverse car search needs to be improved, especially in realizing real-time path guidance for vehicle owners [25][26] . The algorithm commonly used in parking guidance systems is Dijkstra, A-star path-finding algorithm for path planning.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Reverse Car-seeking in Large Underground Parking Lot Based on A Star Algorithm: A Real Case

Wei¹,

Dong²,

Liao³

2020

SRR

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In order to solve the problems of low utilization rate of large parking lots and low efficiency of parking turnover, it is proposed to use A-star algorithm to plan the shortest path for finding a car, and run it in Android system to realize reverse car-searching. By analyzing the current situation of large underground parking lot barriers, A-star algorithm converts the starting point to the destination route into the corresponding parking space to the destination parking space path, calculates the optimal path and provides real-time path car navigation for the vehicle owner. According to the path searched by the A-star algorithm in the Android system, the time spent by the user to blindly search for the vehicle is largely saved, and the parking space utilization rate and the parking turnover rate are effectively improved. Therefore, the research has certain application value in the large parking lots.

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Section: Literature Reviewmentioning

confidence: 99%

Application of Reverse Car-seeking in Large Underground Parking Lot Based on A Star Algorithm: A Real Case

Wei¹,

Dong²,

Liao³

2020

SRR

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“…After these features are calculated, the first step in any face recognition system is to locate a face. Recently, many algorithms on face detection have appeared in the literature [27]. Each of the algorithms has its own strengths and limitations.…”

Section: High-level Featuresmentioning

confidence: 99%

Boosting the Face Recognition Performance of Ensemble Based LDA for Pose, Non-uniform Illuminations, and Low-Resolution Images

2019

KSII TIIS

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Face recognition systems have several potential applications, such as security and biometric access control. Ongoing research is focused to develop a robust face recognition algorithm that can mimic the human vision system. Face pose, non-uniform illuminations, and lowresolution are main factors that influence the performance of face recognition algorithms. This paper proposes a novel method to handle the aforementioned aspects. Proposed face recognition algorithm initially uses 68 points to locate a face in the input image and later partially uses the PCA to extract mean image. Meanwhile, the AdaBoost and the LDA are used to extract face features. In final stage, classic nearest centre classifier is used for face classification. Proposed method outperforms recent state-of-the-art face recognition algorithms by producing high recognition rate and yields much lower error rate for a very challenging situation, such as when only frontal (0 0) face sample is available in gallery and seven poses (0 0 , ±30 0 , ±35 0 , and ±45 0) as a probe on the LFW and the CMU Multi-PIE databases.

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“…Because of the fast development of vehicle proprietorship worldwide lately, vehicle security has become a worry and basic issue. The diminished expense optical gadgets [6].…”

Section: Introductionmentioning

confidence: 99%

Smart Vehicle Parking System Using Computer Vision and Internet of Things (IoT)

Taylor

Ezekiel

Emmah

2021

COMPUTE

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Internet of Things is the interconnectivity between things, individuals and cloud administrations by means of web, which empowers new plans of action. Because of these exchanges, immense volumes of information are smartly created and is shipped off cloud-based server through web; the information is being handled and broken down, bringing about significant and convenient activities for observing the car parking. The serious issue that is arising currently at a worldwide scale and developing dramatically is the gridlock issue brought about by vehicles. A worldwide scale and developing dramatically is the gridlock issue brought about by vehicles. Among that, finding a better parking sparking space in urban areas has become a major problem with an increase of the numbers of vehicles on a daily bases. Therefore making it difficult in having a better and safe parking spot. The system proposes an intelligent smart parking system using computer vision and internet of things. The proposed system starts by acquiring a dataset. The dataset is made up images of various vehicles, which was collected from the faculty of science car park at the Rivers State University, Port Harcourt, Rivers State Nigeria. We proposed two methods for vehicle/parking slot detection. The first method is the use of convolution neural network algorithm which is used with a haar cascade classifier in detection of multiple vehicles in a single picture and video, and put rectangular boxes on identified vehicles. This first method obtained an accuracy of 99.80%. In the second method, we made use of a Mask R-CNN, here we download a pre-trained model weights which was trained on a coco dataset to identify various objects in videos and pictures. The Mask R-CNN model was used to identify various vehicles by putting a bounding box on each of the vehicle detected, but one of the problem of the Mask R-CNN is that it quite slow in training, and it could not really detect all vehicles tested on a high quality high definition video. In summary our, trained model was able to detect vehicles and parking slot on high quality video and it consumes lesser graphic card.

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Towards a fully automated car parking system

Cited by 41 publications

References 34 publications

Application of Reverse Car-seeking in Large Underground Parking Lot Based on A Star Algorithm: A Real Case

Application of Reverse Car-seeking in Large Underground Parking Lot Based on A Star Algorithm: A Real Case

Boosting the Face Recognition Performance of Ensemble Based LDA for Pose, Non-uniform Illuminations, and Low-Resolution Images

Smart Vehicle Parking System Using Computer Vision and Internet of Things (IoT)

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