A Gabor Filter-Based Protocol for Automated Image-Based Building Detection

Abstract

Detecting buildings from high-resolution satellite imagery is beneficial in mapping, environmental preparation, disaster management, military planning, urban planning and research purposes. Differentiating buildings from the images is possible however, it may be a time-consuming or complicated process. Therefore, the high-resolution imagery from satellites needs to be automated to detect the buildings. Additionally, buildings exhibit several different characteristics, and their appearance in these images is unplanned. Moreover, buildings in the metropolitan environment are typically crowded and complicated. Therefore, it is challenging to identify the building and hard to locate them. To resolve this situation, a novel probabilistic method has been suggested using local features and probabilistic approaches. A local feature extraction technique was implemented, which was used to calculate the probability density function. The locations in the image were represented as joint probability distributions and were used to estimate their probability distribution function (pdf). The density of building locations in the image was extracted. Kernel density distribution was also used to find the density flow for different metropolitan cities such as Sydney (Australia), Tokyo (Japan), and Mumbai (India), which is useful for distribution intensity and pattern of facility point f interest (POI). The purpose system can detect buildings/rooftops and to test our system, we choose some crops with panchromatic high-resolution satellite images from Australia and our results looks promising with high efficiency and minimal computational time for feature extraction. We were able to detect buildings with shadows and building without shadows in 0.4468 (seconds) and 0.5126 (seconds) respectively.

Effects of COVID-19 on the Australian Economy: Insights into the Mobility and Unemployment Rates in Education and Tourism Sectors

“…Overall, around 800,000 Australians have lost their jobs since 2020 due to the pandemic. The government has responded to the economic fallout by introducing a wage subsidy scheme, i.e., Job Keeper [13][14][15]. Under this scheme, permanent full-time, part-time, and casual employees who held their jobs for over 12 months were paid $1500 per fortnight to meet their essential expenditures during lockdowns and joblessness [16].…”

Automatic Target Detection from Satellite Imagery Using Machine Learning

“…YOLO uses one network for training and for prediction it also uses one network evaluation for testing of images [ 74 , 75 , 76 ]. YOLO estimates the class probability for each bounding box and predicts 98 bounding boxes for each image in our dataset.…”

Cloud- and Fog-Integrated Smart Grid Model for Efficient Resource Utilisation

“…A revised algorithm for energy management derived on the basis of the renewable energy sources (RES) concept (i.e., PV panels, wind turbine, hydropower systems etc.) and demand response was introduced by [ 59 , 60 ]. A smart grid-based architecture model includes photovoltaic panels, principles of demand response, the sharing of various resources for the provision of load, and state of charge.…”