Arial images are very high resolution. The automation for map generation and semantic segmentation of aerial images are challenging problems in semantic segmentation. The semantic segmentation process does not give us precise details of the remote sensing images due to the low resolution of the aerial images. Hence, we propose an algorithm U-Net Architecture to solve this problem. It is classified into two paths. The compression path (also called: the encoder) is the first path and is used to capture the image’s context. The encoder is just a convolutional and maximal pooling layer stack. The symmetric expanding path (also called: the decoder) is the second path, which is used to enable exact localization by transposed convolutions. This task is commonly referred to as dense prediction, which is completely connected to each other and also with the former neurons which gives rise to dense layers. Thus it is an end-to-end fully convolutional network (FCN), i.e. it only contains convolutional layers and does not contain any dense layer because of which it can accept images of any size. The performance of the model will be evaluated by improving the image using the proposed method U-NET and obtaining an improved image by measuring the accuracy compared with the value of accuracy with previous methods.

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Semantic Segmentation of Aerial Images Using U-Net Architecture

The main factors affecting the performance of Local Water Company (LWC) when managing consumable water distribution in Indonesia are non-revenue water, less water usage effectiveness, less efficiency of billing records and customer complaints about services not becoming available for up to 24 hours. The factor happens because the process is still done manually. So errors and fraud are often found. This research aims to provide a solution by proposing the design of an LWC recording and billing system with a practical and safe prepaid Self-Service method. The prepaid Self-Service process is divided into two main functions. First, the real-time calculation function is designed to solve the efficiency problem in recording water usage. Second, the self-payment token's process is designed to resolve data processing and bill payment constraints. It generated tokens for self-payment token functions built using the Vernam Cipher Cryptographic Algorithm. An Android platform with an Arduino IDE is used in this system. A token will be sent to other devices through Bluetooth serial communication. The results were successfully performed using the Vernam Cipher Cryptographic Algorithm for the self-payment token function. The encryption token consisting of 48 characters can be automatically transferred to other devices using Bluetooth serial communication. The encryption process takes about 0.34 seconds, and the decryption takes about 0.20 seconds.

Analysis and Design of Self-service Local Water Company (LWC) using Vernam Cipher Cryptography Algorithm

Due to the need to protect the information sent over the Internet from being violated by unauthorized persons, many security solutions have appeared to overcome the problems of data leakage. From these solutions is encryption, but once the data is decoded, it will be easy to violate, so to increase the strength of protection, many have appeared. Masking algorithms and methods that extend to digital media copyright protection. In this research, we propose to encrypt and hide a group of images, where four images containing a biography were proposed by securely transferring them within a video of the receiving party. Where the protection process goes through two phases: the encryption phase using the development of the Vernam encryption algorithm, where each image is encrypted using a cut-out image from the video, which is the carrier of confidential data, and the encryption process produces three gray images, as this data is hidden using the least important bit method by masking The data is in random clips inside the video, depending on a secret key between the sender and the receiver, then the same secret key is used in the process of encrypting the video as well, which was used as a cover not to hide the four encrypted images of the CV.

Huda Adil Ali

Papers

Vernam Encryption and Steganography of a Number of Images in the Digital Video