• Title/Summary/Keyword: 파이썬 PyQt

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Cryptft+ : Python/Pyqt based File Encryption & Decryption System Using AES and HASH Algorithm (Crypft+ : Python/PyQt 기반 AES와 HASH 알고리즘을 이용한 파일 암복호화 시스템)

  • Shin, Dongho;Bae, Woori;Shin, Hyeonggyu;Nam, Seungjin;Lee, Hyung-Woo
    • Journal of Internet of Things and Convergence
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    • v.2 no.3
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    • pp.43-51
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    • 2016
  • In this paper, we have developed Crypft+ as an enhanced file encryption/decryption system to improve the security of IoT system or individual document file management process. The Crypft+ system was developed as a core security module using Python, and designed and implemented a user interface using PyQt. We also implemented encryption and decryption function of important files stored in the computer system using AES based symmetric key encryption algorithm and SHA-512 based hash algorithm. In addition, Cx-Freezes module is used to convert the program as an exe-based executable code. Additionally, the manual for understanding the Cryptft+ SW is included in the internal program so that it can be downloaded directly.

A shopping cart system that enables an efficient shopping experience (효율적인 쇼핑 경험을 위한 자동화된 쇼핑 카트 시스템)

  • Jai Soon Baek;Kang Min Lee;Mi So Kang;Tae Hyun Shin;Soo Bin Lee;Min Hyuk Choi;Sung Jin Kim
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.665-667
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    • 2023
  • 본 논문에서는 효율적인 쇼핑 경험을 제공하기 위해 숏카트라는 자동화된 쇼핑 카트 시스템을 제안한다. 숏카트는 사용자의 편의성을 높이기 위해 자동화 기술을 활용하며, 사용자가 상품을 선택하면 카메라를 통해 바코드를 인식하고, Python을 활용하여 바코드값을 읽어온다. 읽어온 바코드 값을 데이터베이스의 바코드 값들과 비교하여 동일한 값을 가진 상품을 사용자의 장바구니에 자동으로 추가한다. 이를 통해 사용자는 편리하게 상품을 선택하고, 계산 과정을 자동화하여 시간을 절약할 수 있다. 또한, GUI 프로그램을 PyQT로 개발하여 사용자에게 시각적으로 장바구니 내용을 표시해 준다.

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Database Generation and Management System for Small-pixelized Airborne Target Recognition (미소 픽셀을 갖는 비행 객체 인식을 위한 데이터베이스 구축 및 관리시스템 연구)

  • Lee, Hoseop;Shin, Heemin;Shim, David Hyunchul;Cho, Sungwook
    • Journal of Aerospace System Engineering
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    • v.16 no.5
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    • pp.70-77
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    • 2022
  • This paper proposes database generation and management system for small-pixelized airborne target recognition. The proposed system has five main features: 1) image extraction from in-flight test video frames, 2) automatic image archiving, 3) image data labeling and Meta data annotation, 4) virtual image data generation based on color channel convert conversion and seamless cloning and 5) HOG/LBP-based tiny-pixelized target augmented image data. The proposed framework is Python-based PyQt5 and has an interface that includes OpenCV. Using video files collected from flight tests, an image dataset for airborne target recognition on generates by using the proposed system and system input.