• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.220-228
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• 2022

Image always carry useful information, detecting a text from scene images is imperative. The proposed work's purpose is to recognize scene text image, example boarding image kept on highways. Scene text detection on highways boarding's plays a vital role in road safety measures. At initial stage applying preprocessing techniques to the image is to sharpen and improve the features exist in the image. Likely, morphological operator were applied on images to remove the close gaps exists between objects. Here we proposed a two phase algorithm for extracting and recognizing text from scene images. In phase I text from scenery image is extracted by applying various image preprocessing techniques like blurring, erosion, tophat followed by applying thresholding, morphological gradient and by fixing kernel sizes, then canny edge detector is applied to detect the text contained in the scene images. In phase II text from scenery image recognized using MSER (Maximally Stable Extremal Region) and OCR; Proposed work aimed to detect the text contained in the scenery images from popular dataset repositories SVT, ICDAR 2003, MSRA-TD 500; these images were captured at various illumination and angles. Proposed algorithm produces higher accuracy in minimal execution time compared with state-of-the-art methodologies.

• International Journal of Computer Science & Network Security
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• 제24권7호
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• pp.143-147
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• 2024

Image noise classification is a classical problem in the field of image processing, machine learning, deep learning and computer vision. In this paper, image noise classification is performed using deep learning. Keras deep learning library of TensorFlow is used for this purpose. 6900 images images are selected from the Kaggle database for the classification purpose. Dataset for labeled noisy images of multiple type was generated with the help of Matlab from a dataset of non-noisy images. Labeled dataset comprised of Salt & Pepper, Gaussian and Sinusoidal noise. Different training and tests sets were partitioned to train and test the model for image classification. In deep neural networks CNN (Convolutional Neural Network) is used due to its in-depth and hidden patterns and features learning in the images to be classified. This deep learning of features and patterns in images make CNN outperform the other classical methods in many classification problems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권5호
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• pp.1938-1962
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• 2015

Security of information during transmission is a major issue in this modern era. All of the communicating bodies want confidentiality, integrity, and authenticity of their secret information. Researchers have presented various schemes to cope with these Internet security issues. In this context, both steganography and cryptography can be used effectively. However, major limitation in the existing steganographic methods is the low-quality output stego images, which consequently results in the lack of security. To cope with these issues, we present an efficient method for RGB images based on gray level modification (GLM) and multi-level encryption (MLE). The secret key and secret data is encrypted using MLE algorithm before mapping it to the grey-levels of the cover image. Then, a transposition function is applied on cover image prior to data hiding. The usage of transpose, secret key, MLE, and GLM adds four different levels of security to the proposed algorithm, making it very difficult for a malicious user to extract the original secret information. The proposed method is evaluated both quantitatively and qualitatively. The experimental results, compared with several state-of-the-art algorithms, show that the proposed algorithm not only enhances the quality of stego images but also provides multiple levels of security, which can significantly misguide image steganalysis and makes the attack on this algorithm more challenging.

• 한국컴퓨터정보학회논문지
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• 제24권11호
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• pp.195-200
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• 2019

이 연구의 목적은 언론 보도 분석을 통해 우리나라에서 경비원에 대한 인식과 이미지를 살펴보고 이를 통해 경비원의 지위와 역할에 대해 살펴보는데 있다. 연구방법은 뉴스 빅데이터 분석이 가능한 빅카인즈를 통해 경비원에 대한 키워드 트랜드와 연관어 분석을 실시하였다. 민간경비의 시대적 구분에 따라 정착기, 성장기(양적), 성장기(질적)으로 구분하여 분석한 결과 범죄, 경비업, 최저임금, 갑질에 관련된 언론의 관심과 노출이 많았던 것으로 나타났지만 범죄예방의 주체가 아닌 범죄와 갑질의 피해자, 경비업무의 애매모함, 최저임금 근무자로 근무환경이 열악한 직업의 이미지로 비춰지는 것으로 나타났다. 앞으로 경비원의 이미지 제고를 위해 경비원의 지위와 업무영역을 확고히 하고 전문성을 높여야 할 것이다.

• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.83-93
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• 2021

COVID-19 poses a major risk to global health, highlighting the importance of faster and proper diagnosis. To handle the rise in the number of patients and eliminate redundant tests, healthcare information exchange and medical data are transmitted between healthcare centres. Medical data sharing helps speed up patient treatment; consequently, exchanging healthcare data is the requirement of the present era. Since healthcare professionals share data through the internet, security remains a critical challenge, which needs to be addressed. During the COVID-19 pandemic, computed tomography (CT) and X-ray images play a vital part in the diagnosis process, constituting information that needs to be shared among hospitals. Encryption and image steganography techniques can be employed to achieve secure data transmission of COVID-19 images. This study presents a new encryption with the image steganography model for secure data transmission (EIS-SDT) for COVID-19 diagnosis. The EIS-SDT model uses a multilevel discrete wavelet transform for image decomposition and Manta Ray Foraging Optimization algorithm for optimal pixel selection. The EIS-SDT method uses a double logistic chaotic map (DLCM) is employed for secret image encryption. The application of the DLCM-based encryption procedure provides an additional level of security to the image steganography technique. An extensive simulation results analysis ensures the effective performance of the EIS-SDT model and the results are investigated under several evaluation parameters. The outcome indicates that the EIS-SDT model has outperformed the existing methods considerably.

• Journal of the Optical Society of Korea
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• 제20권1호
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• pp.42-54
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• 2016

A hybrid color and grayscale images encryption scheme based on the quaternion Hartley transform (QHT), the two-dimensional (2D) logistic map, the double random phase encoding (DRPE) in gyrator transform (GT) domain and the three-step phase-shifting interferometry (PSI) is presented. First, we propose a new color image processing tool termed as the quaternion Hartley transform, and we develop an efficient method to calculate the QHT of a quaternion matrix. In the presented encryption scheme, the original color and grayscale images are represented by quaternion algebra and processed holistically in a vector manner using QHT. To enhance the security level, a 2D logistic map-based scrambling technique is designed to permute the complex amplitude, which is formed by the components of the QHT-transformed original images. Subsequently, the scrambled data is encoded by the GT-based DRPE system. For the convenience of storage and transmission, the resulting encrypted signal is recorded as the real-valued interferograms using three-step PSI. The parameters of the scrambling method, the GT orders and the two random phase masks form the keys for decryption of the secret images. Simulation results demonstrate that the proposed scheme has high security level and certain robustness against data loss, noise disturbance and some attacks such as chosen plaintext attack.

• International Journal of Computer Science & Network Security
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• 제22권1호
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• pp.1-6
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• 2022

Exploration has always been an instinct of humans, and underwater life is as fascinating as it seems. So, for studying flora and fauna below water, there is a need for high-quality images. However, the underwater images tend to be of impaired quality due to various factors, which calls for improved and enhanced underwater images. There are various Histogram Equalization (HE) based techniques which could aid in solving these issues. Classifying the HE methods broadly, there is Global Histogram Equalization (GHE), Mean Brightness Preserving HE (MBPHE), Bin Modified HE (BMHE), and Local HE (LHE). Each of these HE extensions have their own pros and cons and thus, by considering them we have considered BBHE, CLAHE, BPDHE, BPDFHE, and DSIHE enhancement algorithms, which are based on Mean Brightness Preserving HE and Local HE, for this study. The performance is evaluated with non-reference performance measures like Entropy, UCIQE, UICM, and UIQM. In this study, we apply the enhancement algorithms on 300 images from the UIEB benchmark dataset and then apply the techniques of cascading fusion on the best-performing algorithms.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.631-634
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• 2002

In this paper, we propose an improved optical security system using three phase-encoded images and the principle of interference. This optical system based on a Mach-Zehnder interferometer consists of one phase-encoded virtual image to be encrypted and two phase-encoded images, encrypting image and decrypting image, where every pixel in the three images has a phase value of '0' and '$\pi$'. The proposed encryption is performed by the multiplication of an encrypting image and a phase-encoded virtual image which dose not contain any information from the decrypted image. Therefore, even if the unauthorized users steal and analyze the encrypted image, they cannot reconstruct the required image. This virtual image protects the original image from counterfeiting and unauthorized access.. The decryption of the original image is simply performed by interfering between a reference wave and a direct pixel-to-pixel mapping image of the encrypted image with a decrypting image. Both computer simulations and optical experiments confirmed the effectiveness of the proposed optical technique for optical security applications.

• 정보보호학회논문지
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• 제18권3호
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• pp.61-68
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• 2008

본 논문에서는 지문 영상의 품질을 평가하는 새로운 방법을 제안한다. 제안한 방법은 지문 융선의 분포와 방향성, 특징점의 밀도 뿐 아니라 지문의 크기, 위치 등을 분석하여 지문 영상의 품질을 평가하게 된다. 특히 지문의 입력 위치를 분석하여 한쪽으로 치우치거나 일부만 입력된 지문을 걸러냄으로서 인식 성능을 향상시킬 수 있다. 또한 제안한 품질 평가 방법을 다양한 지문 데이터베이스에 적용하여 지문 영상의 품질과 인식 성능 간의 상관도 분석을 수행하였으며, 이를 통하여 인식 성능 향상을 위한 영상의 품질에 대한 임계값을 결정할 수 있었다.

• International Journal of Computer Science & Network Security
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• 제23권10호
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• pp.129-134
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• 2023

The greatest challenge of this century is the protection of stored and transmitted data over the network. This paper provides a new hybrid algorithm designed based on combination algorithms, in the proposed algorithm combined with Hill and the Advanced Encryption Standard Algorithms, to increase the efficiency of color image encryption and increase the sensitivity of the key to protect the RGB image from Keyes attackers. The proposed algorithm has proven its efficiency in encryption of color images with high security and countering attacks. The strength and efficiency of combination the Hill Chipper and Advanced Encryption Standard Algorithms tested by statical analysis for RGB images histogram and correlation of RGB images before and after encryption using hill cipher and proposed algorithm and also analysis of the secret key and key space to protect the RGB image from Brute force attack. The result of combining Hill and Advanced Encryption Standard Algorithm achieved the ability to cope statistically