Color Detection Algorithm Research Articles

Robust Rubik’s Cube Detection Using Hough Transform and Advanced Clustering Functions

Presented paper describes vision-based algorithm for 2D Rubik’s cube state detection suitable for cases in which long-term fixed camera-cube position is not possible. The main focus was to provide a robust algorithm for position and color detection in order to overcome problems observed in previous version. First part of paper describes Hough transform and advanced clustering functions that were used for cube position detection. Described algorithm provides robustness to strong occlusions and various lighting conditions. Second part of paper describes color detection algorithm and problems of prior classification in various color spaces.

Skin Segmentation Using YUV and RGB Color Spaces

Skin detection is used in many applications, such as face recognition, hand tracking, and human-computer interaction. There are many skin color detection algorithms that are used to extract human skin color regions that are based on the thresholding technique since it is simple and fast for computation. The efficiency of each color space depends on its robustness to the change in lighting and the ability to distinguish skin color pixels in images that have a complex background. For more accurate skin detection, we are proposing a new threshold based on RGB and YUV color spaces. The proposed approach starts by converting the RGB color space to the YUV color model. Then it separates the Y channel, which represents the intensity of the color model from the U and V channels to eliminate the effects of luminance. After that the threshold values are selected based on the testing of the boundary of skin colors with the help of the color histogram. Finally, the threshold was applied to the input image to extract skin parts. The detected skin regions were quantitatively compared to the actual skin parts in the input images to measure the accuracy and to compare the results of our threshold to the results of other's thresholds to prove the efficiency of our approach. The results of the experiment show that the proposed threshold is more robust in terms of dealing with the complex background and light conditions than others.

RGB Color Model Based the Fire Detection Algorithm in Video Sequences on Wireless Sensor Network

Since the fire causes serious disasters, fire detection has been an important study to protect human life. Based on the deficiencies of existing fire detection on real-time and monitoring accuracy, the wireless sensor network technique for fire detection was introduced and needed. In this paper, we proposed the fire detection algorithm in video sequences on wireless sensor network. The proposed fire detection algorithm processes visual information acquired through static camera that lets us incorporate the algorithm to CCTV surveillance system, and therefore does not require an additional expanses on conventional fire sensors. Fire detection method based on motion information, any input image, is compared to background in order to identify foreground. Background is statistically modeled by mixture of Gaussians. To detect the foreground of video sequences, the proposed color detection algorithm was performed in RGB space. The procedure of algorithm eliminates all objects that do not fulfill color requirements without fire-like objects. And the change map and blob's area are computed, change map shows temporal variation of pixel between two consecutive binary frames, and percentage area increase or decrease characterizes a fire property for swinging.

Extraction of spatial information for low-bandwidth telerehabilitation applications.

Telemedicine applications, based on two-dimensional (2D) video conferencing technology, have been around for the past 15 to 20 yr. They have been demonstrated to be acceptable for face-to-face consultations and useful for visual examination of wounds and abrasions. However, certain telerehabilitation assessments need the use of spatial information in order to accurately assess the patient's condition and sending three-dimensional video data over low-bandwidth networks is extremely challenging. This article proposes an innovative way of extracting the key spatial information from the patient's movement during telerehabilitation assessment based on 2D video and then presenting the extracted data by using graph plots alongside the video to help physicians in assessments with minimum burden on existing video data transfer. Some common rehabilitation scenarios are chosen for illustrations, and experiments are conducted based on skeletal tracking and color detection algorithms using the Microsoft Kinect sensor. Extracted data are analyzed in detail and their usability discussed.

An Improved Skin Color Detection Algorithm Model

The main objective of designing skin color model is to determine whether the pixel is skin color pixels and generate the skin color mask images. The paper discusses the choise of color space and skin color model designing in skin color detection system, analysis the problems often needed to solve in it and put forward an improved skin color detection algorithm model based on ellipse boundary. The skin color detection experiment is completed. The result of experiment shows the skin color detection algorithm model is good.

Entropy Supported Video Indexing for Content based Video Retrieval

The increased in availability and usage of on-line digital video has created a need of automated video content analysis techniques, including indexing and retrieving. Automation of indexing significantly reduces the processing cost while by minimizing tedious work. Traditional video retrieval methods based on video metadata, fail to meet technical challenges due to large and rapid growth of multimedia data, demanding effective retrieval systems. One of the most popular solutions for indexing is extracting the features of video key frames for developing a Content Based Video Retrieval (CBVR) system. CBVR works more effectively as these deals with content of video rather than video metadata. Various features like color, texture, shape can be integrated and used for video indexing and retrieval. Implemented CBVR system is experimented based on integration of texture, color and edge features for video retrieval. Entropy is a texture descriptor used for key frame extraction and video indexing. However entropy, color (RGB) and edge detection algorithms are used for video retrieval. These features are combined in various ways like entropyedge, entropycolor for result refinement. Dataset is created with the videos from different domains like e-learning, nature, construction etc. By the combination of these features in different ways, we achieved comparative results. Obtained result shows that combining of two or many features gives better retrieval.

배경의 변화에 따른 피부색상 검출 알고리즘의 성능 비교

Accurately extracting skin color regions is very important in various areas such as face recognition and tracking, facial expression recognition, adult image identification, health-care, and so forth. In this paper, we evaluate the performances of several skin color detection algorithms in indoor environments by changing the distance between the camera and the object as well as the background colors of the object. The distance is from 60cm to 120cm and the background colors are white, black, orange, pink, and yellow, respectively. The algorithms that we use for the performance evaluation are Peer algorithm, NNYUV, NNHSV, LutYUV, and Kimset algorithm. The experimental results show that NNHSV, NNYUV and LutYUV algorithm are stable, but the other algorithms are somewhat sensitive to the changes of backgrounds. As a result, we expect that the comparative experimental results of this paper will be used very effectively when developing a new skin color extraction algorithm which are very robust to dynamic real environments.

Reactive behaviours and agent architecture for Sony legged robots to play football

It has been an ultimate long‐term dream in robotics and AI fields to build robotic systems with life‐like appearance, behaviours and intelligence, reflected by many science fiction books and films. This is also an extremely challenging task. This paper introduces our current research efforts to build a multi‐agent system for cooperation and learning of multiple life‐like robots in the RoboCup domain. A behaviour‐based hierarchy is proposed for the Essex Rovers robot football team to achieve intelligent actions in real time, which includes both a neural network‐based color detection algorithm and a fuzzy logic controller. Preliminary results based on legged locomotion experiments of Sony walking robots are presented.