scholarly journals New Stereo Vision Algorithm Composition Using Weighted Adaptive Histogram Equalization and Gamma Correction

2021 ◽  
Vol 15 (3) ◽  
pp. 239-250
Author(s):  
Ahmad Fauzan Kadmin ◽  
Rostam Affendi ◽  
Nurulfajar Abd. Manap ◽  
Mohd Saad ◽  
Nadzrie Nadzrie ◽  
...  
Keyword(s):  
Stereo Vision ◽  
Vision System ◽  
Median Filter ◽  
Histogram Equalization ◽  
Gamma Correction ◽  
Stereo Correspondence ◽  
Disparity Map ◽  
Depth Measurement ◽  
Adaptive Histogram Equalization ◽  
Processing Step

This work presents the composition of a new algorithm for a stereo vision system to acquire accurate depth measurement from stereo correspondence. Stereo correspondence produced by matching is commonly affected by image noise such as illumination variation, blurry boundaries, and radiometric differences. The proposed algorithm introduces a pre-processing step based on the combination of Contrast Limited Adaptive Histogram Equalization (CLAHE) and Adaptive Gamma Correction Weighted Distribution (AGCWD) with a guided filter (GF). The cost value of the pre-processing step is determined in the matching cost step using the census transform (CT), which is followed by aggregation using the fixed-window and GF technique. A winner-takes-all (WTA) approach is employed to select the minimum disparity map value and final refinement using left-right consistency checking (LR) along with a weighted median filter (WMF) to remove outliers. The algorithm improved the accuracy 31.65% for all pixel errors and 23.35% for pixel errors in nonoccluded regions compared to several established algorithms on a Middlebury dataset.

scholarly journals Literature Survey on Stereo Vision Disparity Map Algorithms

2016 ◽  
Vol 2016 ◽  
pp. 1-23 ◽  
Author(s):  
Rostam Affendi Hamzah ◽  
Haidi Ibrahim
Keyword(s):  
Stereo Vision ◽  
Stereo Matching ◽  
Literature Survey ◽  
Processing Unit ◽  
Stereo Correspondence ◽  
Disparity Map ◽  
Central Processing ◽  
Field Programmable ◽  
Processing Module ◽  
Graphical Processing

This paper presents a literature survey on existing disparity map algorithms. It focuses on four main stages of processing as proposed by Scharstein and Szeliski in a taxonomy and evaluation of dense two-frame stereo correspondence algorithms performed in 2002. To assist future researchers in developing their own stereo matching algorithms, a summary of the existing algorithms developed for every stage of processing is also provided. The survey also notes the implementation of previous software-based and hardware-based algorithms. Generally, the main processing module for a software-based implementation uses only a central processing unit. By contrast, a hardware-based implementation requires one or more additional processors for its processing module, such as graphical processing unit or a field programmable gate array. This literature survey also presents a method of qualitative measurement that is widely used by researchers in the area of stereo vision disparity mappings.

Research on People Counting Based on Stereo Vision

2013 ◽  
Vol 373-375 ◽  
pp. 619-623
Author(s):  
Yun Zhou Zhang ◽  
Shou Shuai Xu ◽  
Liang Gao ◽  
Shan Bao Yang ◽  
Xiao Lin Su
Keyword(s):  
Stereo Vision ◽  
Moving Objects ◽  
Feature Matching ◽  
Object Segmentation ◽  
Vision System ◽  
Office Building ◽  
Disparity Map ◽  
Passenger Flow ◽  
The People ◽  
Binocular Vision System

In both industrial field and office building, the accurate statistic of people who enter or leave the elevator has important practical meaning in security and analysis of passenger flow. We present a binocular vision system to count the people pass by. The camera is set in the height of 2.45 meters to monitor the people overhead in order to reduce the overlap of pedestrians. The object segment and tracking method proposed in this paper show good result with the disparity map gained by the dual-camera. Dynamic promotion of threshold is used in the object segmentation. Feature matching is used to track the moving objects. The system can get the number of people accurate and timely. Experiment results show that our system has good performance under relatively complex circumstance.

scholarly journals Automatic Contrast-Limited Adaptive Histogram Equalization With Dual Gamma Correction

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 11782-11792 ◽  
Author(s):  
Yakun Chang ◽  
Cheolkon Jung ◽  
Peng Ke ◽  
Hyoseob Song ◽  
Jungmee Hwang
Keyword(s):  
Histogram Equalization ◽  
Gamma Correction ◽  
Adaptive Histogram Equalization

scholarly journals Image Defogging Framework Using Segmentation and the Dark Channel Prior

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 285
Author(s):  
Sabiha Anan ◽  
Mohammad Ibrahim Khan ◽  
Mir Md Saki Kowsar ◽  
Kaushik Deb ◽  
Pranab Kumar Dhar ◽  
...  
Keyword(s):  
Histogram Equalization ◽  
Homogeneous Region ◽  
Experimental Result ◽  
Dark Channel Prior ◽  
Color Information ◽  
Visual Effects ◽  
Low Contrast ◽  
Adaptive Histogram Equalization ◽  
Processing Step ◽  
Dark Channel

Foggy images suffer from low contrast and poor visibility problem along with little color information of the scene. It is imperative to remove fog from images as a pre-processing step in computer vision. The Dark Channel Prior (DCP) technique is a very promising defogging technique due to excellent restoring results for images containing no homogeneous region. However, having a large homogeneous region such as sky region, the restored images suffer from color distortion and block effects. Thus, to overcome the limitation of DCP method, we introduce a framework which is based on sky and non-sky region segmentation and restoring sky and non-sky parts separately. Here, isolation of the sky and non-sky part is done by using a binary mask formulated by floodfill algorithm. The foggy sky part is restored by using Contrast Limited Adaptive Histogram Equalization (CLAHE) and non-sky part by modified DCP. The restored parts are blended together for the resultant image. The proposed method is evaluated using both synthetic and real world foggy images against state of the art techniques. The experimental result shows that our proposed method provides better entropy value than other stated techniques along with have better natural visual effects while consuming much lower processing time.

scholarly journals Perbandingan Metode Contrast Enhancement pada Citra CT-Scan Kanker Paru-paru

Gravitasi ◽  
2020 ◽  
Vol 19 (2) ◽  
pp. 24-28
Author(s):  
Nurhidayah ◽  
Bannu Abdul Samad ◽  
Bualkar Abdullah
Keyword(s):  
Ct Scan ◽  
Contrast Enhancement ◽  
Mean Square Error ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Histogram Equalization ◽  
Mean Square ◽  
Signal To Noise ◽  
Adaptive Histogram Equalization ◽  
Noise Ratio

Abstrak: Di Indonesia kanker paru menjadi penyebab kematian kedua setelah kanker payudara. Angka mortalitas yang cukup tinggi, maka penentuan diagnosis lebih awal memegang peranan yang sangat penting dalam manajemen terapi. Kelemahan CT-Scan dalam mendiagnosa kanker paru-paru disebabkan oleh kontras citra yang rendah dan derau pada citra. Pada penelitian ini akan membandingkan metode contrast enhancement berbasis histogram equalization dan contrast limited adaptive histogram equalization untuk meningkatkan kualitas citra dengan menggunakan software Matlab. Namun, sebelumnya dilakukan reduksi noise dengan menggunakan metode median filter. Kinerja dari setiap metode dihitung dengan mencari nilai MSE (Mean Square Error) dan PSNR (Peak Signal to Noise Ratio) citra. Dari nilai MSE dan PSNR yang di dapatkan diperoleh nilai MSE dan PSNR terbaik pada metode contrast limited adaptive histogram equalization dengan nilai 653,434 dB dan 245,547 dB.

Robot Stereo Vision Guidance System Based on Attention Mechanism

2013 ◽  
Vol 385-386 ◽  
pp. 708-711 ◽  
Author(s):  
Long Yang ◽  
Nan Feng Xiao
Keyword(s):  
Stereo Vision ◽  
Rotation Angle ◽  
Vision System ◽  
Attention Mechanism ◽  
Guidance System ◽  
Disparity Map ◽  
Joint Rotation ◽  
Vision Guidance ◽  
Stereo Calibration ◽  
Coordinates Transformation

Add attention mechanism into traditional robot stereo vision system, thus got the possible workpiece position quickly by saliency image, highly accelerate the computing process. First, to get the camera intrinsic matrix and extrinsic matrix, camera stereo calibration needed be done. Then use those parameter matrixes to rectify the newly captured images, disparity map can be got based on the OpenCV library, meanwhile, saliency image was computed by Itti algorithm. Workpiece spatial pose to left camera coordinates can be got with triangulation measurement principal. After a series of coordinates transformation workpiece spatial pose to world coordinates can be got. With the robot inverse solution function, the robot joint rotation angle can be got thus driver the robot to work. At last, experiment results show the effectiveness of this method.

Sign in / Sign up

Export Citation Format

Share Document