Browsing by Subject "Color image processing"

Now showing 1 - 8 of 8

Open Access
Adaptive methods for dithering color images
(Institute of Electrical and Electronics Engineers, 1997-07) Akarun, L.; Yardımcı, Y.; Çetin, A. Enis
Most color image printing and display devices do not have the capability of reproducing true color images. A common remedy is the use of dithering techniques that take advantage of the lower sensitivity of the eye to spatial resolution and exchange higher color resolution with lower spatial resolution. In this paper, an adaptive error diffusion method for color images is presented. The error diffusion filter coefficients are updated by a normalized least mean square-type (LMS-type) algorithm to prevent textural contours, color impulses, and color shifts, which are among the most common side effects of the standard dithering algorithms. Another novelty of the new method is its vector character: Previous applications of error diffusion have treated the individual color components of an image separately. Here, we develop a general vector approach and demonstrate through simulation studies that superior results are achieved.
Open Access
Flame detection in video using hidden Markov models
(IEEE, 2005) Töreyin, B. Uğur; Dedeoğlu, Yiğithan; Çetin, A. Enis
This paper proposes a novel method to detect flames in video by processing the data generated by an ordinary camera monitoring a scene. In addition to ordinary motion and color clues, flame flicker process is also detected by using a hidden Markov model. Markov models representing the flame and flame colored ordinary moving objects are used to distinguish flame flicker process from motion of flame colored moving objects. Spatial color variations in flame are also evaluated by the same Markov models, as well. These clues are combined to reach a final decision. False alarms due to ordinary motion of flame colored moving objects are greatly reduced when compared to the existing video based fire detection systems.
Open Access
A histogram-based approach for object-based query-by-shape-and-color in image and video databases
(Elsevier, 2005) Şaykol, E.; Güdükbay, Uğur; Ulusoy, Özgür
Considering the fact that querying by low-level object features is essential in image and video data, an efficient approach for querying and retrieval by shape and color is proposed. The approach employs three specialized histograms, (i.e. distance, angle, and color histograms) to store feature-based information that is extracted from objects. The objects can be extracted from images or video frames. The proposed histogram-based approach is used as a component in the query-by-feature subsystem of a video database management system. The color and shape information is handled together to enrich the querying capabilities for content-based retrieval. The evaluation of the retrieval effectiveness and the robustness of the proposed approach is presented via performance experiments. © 2005 Elsevier Ltd. All rights reserved.
Open Access
Person search made easy
(Springer, Berlin, Heidelberg, 2005) İkizler, Nazlı; Duygulu, Pınar
In this study, we present a method to extensively reduce the number of retrieved images and increase the retrieval performance for the person queries on the broadcast news videos. A multi-modal approach which integrates face and text information is proposed. A state-of-the-art face detection algorithm is improved using a skin color based method to eliminate the false alarms. This pruned set is clustered to group the similar faces and representative faces are selected from each cluster to be provided to the user. For six person queries of TRECVID2004, on the average, the retrieval rate is increased from 8% to around 50%, and the number of images that the user has to inspect are reduced from hundreds and thousands to tens. © Springer-Verlag Berlin Heidelberg 2005.
Open Access
QR-RLS algorithm for error diffusion of color images
(SPIE, 2000) Unal, G. B.; Yardimci, Y.; Arıkan, Orhan; Çetin, A. Enis
Printing color images on color printers and displaying them on computer monitors requires a significant reduction of physically distinct colors, which causes degradation in image quality. An efficient method to improve the display quality of a quantized image is error diffusion, which works by distributing the previous quantization errors to neighboring pixels, exploiting the eye's averaging of colors in the neighborhood of the point of interest. This creates the illusion of more colors. A new error diffusion method is presented in which the adaptive recursive least-squares (RLS) algorithm is used. This algorithm provides local optimization of the error diffusion filter along with smoothing of the filter coefficients in a neighborhood. To improve the performance, a diagonal scan is used in processing the image.
Open Access
Real-time smoke and flame detection in video
(IEEE, 2005) Töreyin, B. Uğur; Dedeoğlu, Yiğithan; Çetin, A. Enis
A novel method to detect smoke and/or flame by processing the video data generated by an ordinary camera monitoring a scene is proposed. It is assumed the camera is stationary. Since the smoke is semi-transparent, edges of image frames start loosing their sharpness and this leads to a decrease in the high frequency content of the image. To determine the smoke, the background of the scene is estimated and decrease of high frequency energy of the scene is monitored using the spatial wavelet transforms of the current and the background images. For the detection of flames, in addition to ordinary motion and color clues, flicker analysis is also carried out by analyzing the video in wavelet domain. These clues are combined to reach a final decision.
Open Access
Superior warm-White light-emitting diodes integrated with quantum dot nanophosphors for high luminous efficacy and color rendering
(Optical Society of America, 2011) Nizamoğlu, Sedat; Erdem, Talha; Sun, X. W.; Demir, Hilmi Volkan
Quantum dot nanophoshor hybridized warm-white LEDs are reported to exhibit high photometric performance of luminous efficacy exceeding 350 lm/Wopt and color rendering index close to 90 at correlated color temperatures <3000 K. ©2011 Optical Society of America.
Open Access
Wavelet based detection of moving tree branches and leaves in video
(IEEE, 2006-05) Töreyin, B. Uğur; Çetin, A. Enis
A method for detection of tree branches and leaves in video is proposed. It is observed that the motion vectors of tree branches and leaves exhibit random motion. On the other hand regular motion of green colored objects has well-defined directions. In this paper, the wavelet transform of motion vectors are computed and objects are classified according to the wavelet coefficients of motion vectors. Color information is also used to reduce the search space in a given image frame of the video. Motion trajectories of moving objects are modeled as Markovian processes and Hidden Markov Models (HMMs) are used to classify the green colored objects in the final step of the algorithm. © 2006 IEEE.