%0 Conference Proceedings
%T Automatic Detection of Buildings Using High Resolution Images for Medium Density Regions
%+ Babasaheb Bhimrao Ambedkar Bihar University
%A Kirwale, Karuna, Sitaram
%A Kawathekar, Seema, S.
%A Deshmukh, Ratnadeep R.
%Z Part 1: Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT)
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 4th International Conference on Computational Intelligence in Data Science (ICCIDS)
%C Chennai, India
%Y Vallidevi Krishnamurthy
%Y Suresh Jaganathan
%Y Kanchana Rajaram
%Y Saraswathi Shunmuganathan
%I Springer International Publishing
%3 Computational Intelligence in Data Science
%V AICT-611
%P 125-131
%8 2021-03-18
%D 2021
%R 10.1007/978-3-030-92600-7_12
%K Automatic building detection
%K Morphological operation
%Z Computer Science [cs]Conference papers
%X As the construction material of the building is different hence building detection is critical task from the HRI. The image qualities, resolution, weather type of image sensor are important factors to produce accuracy. Building detection in dense urban areas having problems due to factors like shape, size, color and texture, and image sensor. For the find, the building has to consider the characters of the building like contrast, shape, and the building allocation in high, low, and medium density. In the present study, the mathematical morphological operation is used for the separation of the building. The building is indicated with a boundary.
%G English
%Z TC 12
%2 https://inria.hal.science/hal-03772931/document
%2 https://inria.hal.science/hal-03772931/file/512058_1_En_12_Chapter.pdf
%L hal-03772931
%U https://inria.hal.science/hal-03772931
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC12
%~ IFIP-ICCIDS
%~ IFIP-AICT-611