Parking Lot Occupancy Detection Using Digital Image Processing
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Solution Overview
Problem
Current parking space availability detection systems are inefficient and costly, lacking automation, which contributes to traffic congestion and fuel consumption in densely populated areas, as they rely on manual processes and expensive sensor installations.
Innovation Solution
A method and system using digital image processing that determines parking lot occupancy by obtaining a layout, estimating parking space volume, classifying pixels using vehicle detectors, and computing occupancy probabilities with a spatially varying membership probability density function, allowing for easy deployment of camera-based systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If parking sensors are used for automatic detection, then detection accuracy is improved, but installation cost and complexity increase significantly
Solution Approach 1:
The patent replaces mechanical sensor systems with an optical imaging system. Instead of using physical sensors embedded in parking spaces, the invention uses digital cameras to capture images and processes them through image processing algorithms to detect parking space occupancy, thereby eliminating the need for complex sensor installations while maintaining detection capability
Solution Approach 2:
The patent creates a digital copy of the parking lot environment through camera imaging. By capturing visual information and processing it to identify vehicles and parking spaces, the system replicates the detection function without requiring physical sensors in each parking space, thus reducing installation complexity
2Device complexity
If manual parking enforcement processes are used, then system cost is reduced, but enforcement efficiency and effectiveness decrease
Solution Approach 1:
The patent implements self-service through automated image processing. The system automatically captures images, processes them to detect occupancy status, and provides enforcement information without requiring manual intervention. This automation maintains low system cost while dramatically improving enforcement efficiency and effectiveness
Solution Approach 2:
The patent replaces manual enforcement processes with automated computational processing. Instead of manual monitoring and enforcement, the system uses image processing algorithms to automatically determine parking status and provide enforcement information, thereby improving productivity while keeping costs low
3Device complexity
If camera-based systems are deployed for parking detection, then installation cost is reduced and versatility is improved, but occupancy determination accuracy becomes challenging
Solution Approach 1:
The patent uses optical imaging and computational algorithms to replace complex sensor systems. By capturing images and processing them through developed algorithms that consider camera position, viewing angle, and image data, the system achieves accurate occupancy determination at low installation cost
Solution Approach 2:
The patent employs multiple parameters including camera position, viewing angle, and processed image data to accurately determine occupancy. By considering these varying parameters and using them in computational algorithms, the system maintains high accuracy while keeping the system simple and cost-effective
Data Source
AI summary
Described herein is a method of determining parking lot occupancy from digital images, including a set-up procedure that includes receiving a layout of a parking lot and estimating parking space volume for at least one viewing angle and the probability that an observed pixel belongs to the parking space volume. The method further includes acquiring one or more image frames of the parking lot from at least one digital camera; performing pixel classification using a vehicle detector on the acquired image frames to determine a likelihood that a pixel belongs to a vehicle; computing a probability that a parking space is occupied by a vehicle based on a spatially varying membership probability density function and a likelihood of vehicle pixels within a region of interest; and determining parking lot vacancy via a comparison of the computed probability that a parking space is occupied by a vehicle to a pre-determined threshold.