Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Myeong-jin Lee is active.

Publication


Featured researches published by Myeong-jin Lee.


Sensors | 2015

Step Detection Robust against the Dynamics of Smartphones.

Hwan-hee Lee; Suji Choi; Myeong-jin Lee

A novel algorithm is proposed for robust step detection irrespective of step mode and device pose in smartphone usage environments. The dynamics of smartphones are decoupled into a peak-valley relationship with adaptive magnitude and temporal thresholds. For extracted peaks and valleys in the magnitude of acceleration, a step is defined as consisting of a peak and its adjacent valley. Adaptive magnitude thresholds consisting of step average and step deviation are applied to suppress pseudo peaks or valleys that mostly occur during the transition among step modes or device poses. Adaptive temporal thresholds are applied to time intervals between peaks or valleys to consider the time-varying pace of human walking or running for the correct selection of peaks or valleys. From the experimental results, it can be seen that the proposed step detection algorithm shows more than 98.6% average accuracy for any combination of step mode and device pose and outperforms state-of-the-art algorithms.


IEEE Transactions on Consumer Electronics | 2012

Multi-object tracking coprocessor for multi-channel embedded DVR systems

Seajin Kim; Byung-jin Lee; Jae-won Jeong; Myeong-jin Lee

In this paper, the architecture of a video analytics coprocessor is proposed for multi-channel embedded digital video recorder (DVR) systems. A reference video analytics algorithm is proposed for multi-object tracking and is divided into independent processing steps based on data flow. Each step is designed in hardware or software considering its computational complexity and required system resources. Pixelwise processing requiring a large amount of computational resources, such as frame difference and background modeling, are designed as hardware with embedded direct memory access (DMA) controllers. A single-pass connected component labeling (CCL) is designed as a hardware targeting real-time processing of stream input. High-level tasks such as object filtering, frame-based control of hardware modules, and communication with an external host are designed with software on an embedded processor. Object tracking and event detection are designed with software on a host processor. Considering both the bandwidth required for frame processing and the bandwidth available by memory buses, the architecture of a 4-channel video analytics coprocessor is explored. It is finally implemented on a field-programmable gate arrays (FPGA) device, integrated into a conventional DVR system, and verified as to its functions and performance. It can provide video analysis functions to conventional DVR system-on-chip (SoC), and can lessen the cost of real-time video monitoring at remote monitoring centers.


international conference on electronics and information engineering | 2010

Automated recommendation of initial mass positions for mass segmentation in digital mammograms

Bong-Ryul Lee; Jong-doo Lee; Myeong-jin Lee

The performance of mass segmentation is greatly influenced by an initial position of a mass. Some researchers performed mass segmentation with the initial position of a mass given by radiologists. The purpose of our research is to find the initial position for mass segmentation and to notify the segmented mass to radiologists without any additional information on mammograms. The proposed system consists of breast segmentation by region growing and opening operations, decision of an initial seed with characteristics of masses, and mass segmentation by a level set segmentation. A seed for mass segmentation is set based on mass scoring measure calculated by block-based variances and masked information in a sub-sampled mammogram. We used a DDSM database to evaluate the system, and the accuracy of mass segmentation is 78% sensitivity at 4 FP/image.


Sensors | 2015

Unified camera tamper detection based on edge and object information.

Gil-beom Lee; Myeong-jin Lee; Jongtae Lim

In this paper, a novel camera tamper detection algorithm is proposed to detect three types of tamper attacks: covered, moved and defocused. The edge disappearance rate is defined in order to measure the amount of edge pixels that disappear in the current frame from the background frame while excluding edges in the foreground. Tamper attacks are detected if the difference between the edge disappearance rate and its temporal average is larger than an adaptive threshold reflecting the environmental conditions of the cameras. The performance of the proposed algorithm is evaluated for short video sequences with three types of tamper attacks and for 24-h video sequences without tamper attacks; the algorithm is shown to achieve acceptable levels of detection and false alarm rates for all types of tamper attacks in real environments.


international conference on consumer electronics | 2014

Low-complexity camera tamper detection based on edge information

Gil-beom Lee; Youn-Chul Shin; Joo-heon Park; Myeong-jin Lee

A low-complexity algorithm for camera tamper detection is proposed which can detect various types of tamper attacks based on edge information. The performance of the proposed algorithm is evaluated for three types of tamper attacks and shown to achieve acceptable level of accuracy for all types of tamper attacks.


Sensors | 2017

Shadow Detection Based on Regions of Light Sources for Object Extraction in Nighttime Video

Gil-beom Lee; Myeong-jin Lee; Woo-Kyung Lee; Joo-heon Park; Tae-Hwan Kim

Intelligent video surveillance systems detect pre-configured surveillance events through background modeling, foreground and object extraction, object tracking, and event detection. Shadow regions inside video frames sometimes appear as foreground objects, interfere with ensuing processes, and finally degrade the event detection performance of the systems. Conventional studies have mostly used intensity, color, texture, and geometric information to perform shadow detection in daytime video, but these methods lack the capability of removing shadows in nighttime video. In this paper, a novel shadow detection algorithm for nighttime video is proposed; this algorithm partitions each foreground object based on the object’s vertical histogram and screens out shadow objects by validating their orientations heading toward regions of light sources. From the experimental results, it can be seen that the proposed algorithm shows more than 93.8% shadow removal and 89.9% object extraction rates for nighttime video sequences, and the algorithm outperforms conventional shadow removal algorithms designed for daytime videos.


signal processing systems | 2016

A Single-Pass Connected Component Labeler without Label Merging Period

Jae-won Jeong; Gil-beom Lee; Myeong-jin Lee; Jae-Gon Kim

In this paper, for real-time multi-channel video analytics, an architecture of a single-pass connected component labeler without label merging period is proposed; this structure can handle multiple video channels from incoming video signals or from memory. During the line scan period, after determining an event based on the 8-connectivity check of incoming pixels, an 8-connectivity checker notifies all the label registers inside a label shift register of the event and the control signals for label handling. Each label register takes a label input either normally from the shifted label in the label shift register, or from the merging label without additional cycles for the label merging event. A label stack is designed for efficient label allocation with label reuse. An information extractor calculates bounding boxes and centers of gravity for labeled objects using the information from the 8-connectivity checker and the pixel counter. The proposed architecture is finally implemented on a field programmable gate array (FPGA) device, integrated into a video analytics system, and verified as to its functions and performance. More than 28 % of the memory usage by conventional architectures is reduced in the proposed architecture for the same maximum number of labels in video surveillance environments.


international conference on consumer electronics | 2012

Intelligent video co-processor for embedded DVR SoC

Seajin Kim; Byung-jin Lee; Myeong-jin Lee

Most of embedded DVR systems have limited functions for intelligent video processing. In this paper, we propose architecture of an intelligent video processing system for embedded DVR systems. It consists of a conventional DVR host system and an intelligent video co-processor system. The co-processor system consists of an embedded processor and several primitive functional units for intelligent video processing, and can be connected to a host DVR system via an external bus interface. The proposed video processing system can perform video surveillance operations for four input video channels in real-time, and can provide a host DVR system with object information for further processing.


Journal of Broadcast Engineering | 2010

Distributed Video Coding Based on Selective Block Encoding Using Feedback of Motion Information

Jin-Soo Kim; Jae-Gon Kim; Kwang-Deok Seo; Myeong-jin Lee

Recently, DVC (Distributed Video Coding) techniques are drawing a lot of interests as one of the future research works to achieve low complexity encoding in various applications. But, due to the limited computational complexity, the performances of DVC algorithms are inferior to those of conventional international standard video coders, which use zig-zag scan, run length code, entropy code and skipped macroblock. In this paper, in order to overcome the performance limit of the DVC system, the distortion for every block is estimated when side information is found at the decoder and then we propose a new selective block encoding scheme which provides the encoder side with the motion information for the highly distorted blocks and then allows the sender to encode the motion compensated frame difference signal. Through computer simulations, it is shown that the coding efficiency of the proposed scheme reaches almost that of the conventional inter-frame coding scheme.


international conference on information networking | 2017

Joint Distortion-Energy control for energy harvesting video sensor nodes

Hwan-hee Lee; Chang-hyun Lee; Myeong-jin Lee

A joint Distortion-Energy (D-E) control method for perpetual energy harvesting video sensor node is proposed. Its objective is to minimize the average distortion of compressed video without energy depletion by exploring D-E relation and energy harvesting prediction method. The proposed method is performed by controlling some D-E control parameters such as the quantization parameter, frame rate, and operating frequency under the delay and energy constraints for perpetual operation. The performance of the proposed method was compared with those of various modes with the fixed frame rate and the perfect harvested energy prediction. The proposed method guaranteed perpetual operation of a video sensor node with acceptable video quality for several days.

Collaboration


Dive into the Myeong-jin Lee's collaboration.

Top Co-Authors

Avatar

Gil-beom Lee

Korea Aerospace University

View shared research outputs
Top Co-Authors

Avatar

Chang-hyun Lee

Korea Aerospace University

View shared research outputs
Top Co-Authors

Avatar

Hwan-hee Lee

Korea Aerospace University

View shared research outputs
Top Co-Authors

Avatar

Joo-heon Park

Korea Aerospace University

View shared research outputs
Top Co-Authors

Avatar

Bong-Ryul Lee

Korea Aerospace University

View shared research outputs
Top Co-Authors

Avatar

Jae-won Jeong

Korea Aerospace University

View shared research outputs
Top Co-Authors

Avatar

Woo-Kyung Lee

Korea Aerospace University

View shared research outputs
Top Co-Authors

Avatar

Youn-Chul Shin

Korea Aerospace University

View shared research outputs
Top Co-Authors

Avatar

Byung-jin Lee

Korea Aerospace University

View shared research outputs
Top Co-Authors

Avatar

Jae-Gon Kim

Hanbat National University

View shared research outputs
Researchain Logo
Decentralizing Knowledge