• Journal of Internet Computing and Services
• /
• v.20 no.6
• /
• pp.29-36
• /
• 2019

When dealing with outdoor images in a variety of computer vision applications, the presence of shadow degrades performance. In order to understand the information occluded by shadow, it is essential to remove the shadow. To solve this problem, in many studies, involves a two-step process of shadow detection and removal. However, the field of shadow detection based on CNN has greatly improved, but the field of shadow removal has been difficult because it needs to be restored after removing the shadow. In this paper, it is assumed that shadow is detected, and shadow-less image is generated by using original image and shadow mask. In previous methods, based on CGAN, the image created by the generator was learned from only the aspect of the image patch in the adversarial learning through the discriminator. In the contrast, we propose a novel method using a discriminator that judges both the whole image and the local patch at the same time. We not only use the residual generator to produce high quality images, but we also use joint loss, which combines reconstruction loss and GAN loss for training stability. To evaluate our approach, we used an ISTD datasets consisting of a single image. The images generated by our approach show sharp and restored detailed information compared to previous methods.

• Journal of Information Technology Services
• /
• v.15 no.3
• /
• pp.33-50
• /
• 2016

In a dynamic IT environment, employees often utilize external IT resources to work more efficiently and flexibly. However, the use of external IT resources beyond its control may cause difficulties in the company. This is known as "Shadow IT." In spite of efficiency gains or cost savings, Shadow IT presents problems for companies such as the outflow of enterprise data. To address these problems, appropriate measures are required to maintain a balance between flexibility and control. Therefore, in this study, we developed a new information security management system called AIIMS (Advanced IT service & Information security Management System) and the Shadow IT Evaluation Model. The proposed model reflects a Shadow IT's attributes such as innovativeness, effectiveness, and ripple effect. AIIMS consists of five fields: current analysis; Shadow IT management plans; management process; education and training; and internal audit. There are additional management items and sub-items within these five fields. Using AIIMS, we expect to not only mitigate the potential risks of Shadow IT but also create successful business outcomes. Now is the time to draw to the Light in the Shadow IT.

• The Journal of Information Systems
• /
• v.30 no.1
• /
• pp.105-121
• /
• 2021

Purpose Today, through digital services, many people enjoy a conveient and comfortable life. Nevertheless, it is easy to find people in our daily lives who are buried in work without any payment that we did not do before digital services. Such un-payed works under digital environment are called digital shadow works. The purpose of this study is to classification and dynamics of digital shadow works and to suggest research direction. Design/methodology/approach Based on two dimension, voluntary participation ('should' type and 'want' type) and work orientation (management-operation), digital shadow works were classified into four categories - chore, makeup, routine, and quest. Findings In digital shadow work there are four types of dynamics - routine and quest, makeup and chore, makeup and quest, and quest and actions in offline. According to the classification and analysis of dynamics, three research directions in digital shadow work are suggested and discussed- digital shadow works operation mechanism considering dynamics, expansion of existing user theories based on survey method by digital shadow works and social influences by digital shadow works.

• Korean Journal of Remote Sensing
• /
• v.16 no.3
• /
• pp.235-242
• /
• 2000

This paper presents a method to detect buildings using shadow information in satellite imagery. We classify image into three categories of building region, shadow region and background region to find buildings with consistent intensity. After the removal of noises in building regions and shadow regions, buildings adjacent to shadow regions are detected using the constraint of building and shadow sizes. The algorithm has been applied to KOMPSAT and SPOT images and the result showed buildings are efficiently detected.

• The Journal of Information Systems
• /
• v.31 no.3
• /
• pp.89-108
• /
• 2022

Purpose The purpose of this study is to clarify the conceptualizations of mandatory and reward that have come into focus in the definition of digital shadow work. And explore how users in a shared services environment view cost and coercion from the perspective of digital shadow work. Design/methodology/approach We conducted one-on-one interviews with 4 participants, with each interview being an average of 25 minutes. Based on literature review, stakeholder observation, and interviews on digital shadow work so far, very objective results can be derived through triangulation based on the basis of multiple sources. Findings According to the results of the preliminary study, there are some rewards for each type of digital shadow work, but time saving and service convenience are considered more than financial rewards. Unfair demands in determining whether to implement them in consideration of the difficulty and expected benefits of the demanding digital work can cause dissatisfaction with the service. Academic implications and future research directions are also discussed.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2003.04a
• /
• pp.187-190
• /
• 2003

Due to complexity of diverse features in urban area, accurate feature extraction is laborious task in aerial and satellite imagery. Especially occlusion by buildings, and image distortion of shadow effects make processing more difficult work. In this study, algorithm was presented to correct of shadow effects in aerial color images. This algorithm enables user to accurately interpretate urban information by correction of shadow effects in aerial color images

• Journal of Internet Computing and Services
• /
• v.21 no.5
• /
• pp.49-56
• /
• 2020

Detecting shadows in images and restoring or removing them was a very challenging task in computer vision. Traditional researches used color information, edges, and thresholds to detect shadows, but there were errors such as not considering the penumbra area of shadow or even detecting a black area that is not a shadow. Deep learning has been successful in various fields of computer vision, and research on applying deep learning has started in the field of shadow detection and removal. However, it was very difficult and time-consuming to collect data for network learning, and there were many limited conditions for shooting. In particular, it was more difficult to obtain shadow data from buildings and satellite images, which hindered the progress of the research. In this paper, we propose a method for generating shadow data from buildings and satellites using Unity3D. In the virtual Unity space, 3D objects existing in the real world were placed, and shadows were generated using lights effects to shoot. Through this, it is possible to get all three types of images (shadow-free, shadow image, shadow mask) necessary for shadow detection and removal when training deep learning networks. The method proposed in this paper contributes to helping the progress of the research by providing big data in the field of building or satellite shadow detection and removal research, which is difficult for learning deep learning networks due to the absence of data. And this can be a suboptimal method. We believe that we have contributed in that we can apply virtual data to test deep learning networks before applying real data.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.4
• /
• pp.2042-2059
• /
• 2019

Digital shadow puppet has traditionally relied on expensive motion capture equipments and complex design. In this paper, a low-cost driven technique is presented, that captures human pose estimation data with simple camera from real scenarios, and use them to drive virtual Chinese shadow play in a 2.5D scene. We propose a special method for extracting human pose data for driving virtual Chinese shadow play, which is called 2.5D human pose estimation. Firstly, we use the 3D human pose estimation method to obtain the initial data. In the process of the following transformation, we treat the depth feature as an implicit feature, and map body joints to the range of constraints. We call the obtain pose data as 2.5D pose data. However, the 2.5D pose data can not better control the shadow puppet directly, due to the difference in motion pattern and composition structure between real pose and shadow puppet. To this end, the 2.5D pose data transformation is carried out in the implicit pose mapping space based on self-network and the final 2.5D pose expression data is produced for animating shadow puppets. Experimental results have demonstrated the effectiveness of our new method.

• Proceedings of the KSRS Conference
• /
• 2008.10a
• /
• pp.371-374
• /
• 2008

In very high-spatial resolution remote sensing imagery, it is difficult to extract the feature information of various objects because of occlusion and shadows. Moreover, various and feeble information within shadows can be of use in GIS-based applications and remote sensing analysis. In this paper, we developed a radiometric restoration method for shadow areas using KOMPSAT-2 satellite image. After detecting the shadow, non-shadow pixels nearby are extracted using a morphological filter. An iterative linear regression method is applied to calculate the relationship between shadow and non-shadow pixels. The shadows are restored by the parameters of the linear regression algorithm. Tests show that recovery of shadowed areas by our method leads to improved image quality.

• Proceedings of the Korean Information Science Society Conference
• /
• 2003.10c
• /
• pp.319-321
• /
• 2003

모바일 컴퓨팅 환경은 크게 모바일 노드, 무선망, 그리고 이동성이라는 기술로 이루어진다. 이음새없는 (seamless) 이동성을 제공하기 위한 기존의 Shadow Registration 방법은 핸드오프가 발생하기 이전에 이웃한 모든 노드들(AAAF/sbu n/)에게 모바일 노드의 관련 정보를 사전등록(Shadow Registration)하는 방법을 제안하여 핸드오프 이후에 발생하는 끊김이나 지연을 방지하였다. 그러나 이러한 Shadow Registration의 경우 백본 네트워크에 불필요한 트래픽 발생 및 데이터 관리라는 문제를 야기시킨다. 본 논문은 이러한 문제점들을 개선하고자 새롭게 사전등록 트리거 영역(STR: Shadow Trigger Region)을 설정하고, STR 내에 모바일 노드(MN)가 위치할 경우 MN의 이동 방향을 이용하여 최소한의 사전등록영역(SRR: Shadow Registration Region)을 찾아내는 방법을 제안한다. 결과적으로 제안된 SRR 은 최대 2 개의 이웃노드(AAAF$_2$)에게만 사전등록을 요청하면 되므로, 기존의 방법에 비해 최대 ∑(n­2)번의 사전등록 횟수를 줄이면서 끊김과 지연도 방지할 수 있는 효과적인 방법이다.