Vehicle Counting and Classification Using Kalman Filter and Pixel Scanner Technique and its verification with Optical Flow Estimation

Dr. H.S. Mohana; G. Shivakumar; Aswatha Kumar

Vehicle Counting and Classification Using Kalman Filter and Pixel Scanner Technique and its verification with Optical Flow Estimation

Dr. H.S. Mohana * §

Contact

G. Shivakumar

Contact

Aswatha Kumar

Contact

§ Malnad College of Engineering, Hassan, India

Vehicle Counting and Classification Using Kalman Filter and Pixel Scanner Technique and its verification with Optical Flow Estimation

Article Fingerprint

ReserarchID

CSTVX2PN

Vehicle Counting and Classification Using Kalman Filter and Pixel Scanner Technique and its verification with Optical Flow Estimation Banner

Key Research Insights

Synthesized scholarly intelligence & interactive research assistant

Abstract

Vehicle tracking is important in traffic monitoring systems. The behaviors of regions of moving vehicles are complicated, since the regions may combine or break during the tracking due to mistakes in vehicle detection and tracking or vehicles’ overlapping with each other, and as a result, region matching simply according to similarities between successive frames is not enough to achieve reliable results. This paper proposes a novel tracking strategy that can robustly track and classify the objects within a fixed environment. We define a robust model-based tracker and classifier using kalman filtering combined with pixel scanner. The tracking is done by fitting successively more elaborate models on the tracked region and the segmentation is done by extracting the regions of the image that are consistent with the computed model of the target. We adopt a competitive and efficient dynamic Kalman filtering to adaptively update the object model by adding new stable features as well as deleting inactive features. In the next stage we need to check each and every frame for object recognition. This work introduce a diagonal pixel scanner to identify the objects. The result is verified further by implementing optical flow analysis. The tracking, counting and classification of object/vehicle have produced very consistent result. The average accuracy with short length video clipping is greater than 98%.

References

10 Cites in Article

Reference Format

Ching-Po Lin,Jen Tai,Kai-Tai Song (2003). Traffic Monitoring Based On Real Time Image Tracking.
Feng Yi-Wei,Guo Ge,Zhu Chao-Qun (2008). Object Tracking by Kalman Filtering and Recursive Least Squares Based on 2D Image Motion.
Gang-Yi Jiang,Mei Yu,Sheng-Nan Wang,Rang-Ding Wang (2005). New Approach To Vehicle Tracking Based On Region Processing.
K Kiratiratanapruk,Supakorn Siddhichai (2009). Practical Application for Vision-Based Traffic Monitoring System.
Fei Zhu (2009). A Video-Based Traffic Congestion Monitoring System Using Adaptive Background Subtraction.
Belle Tseng,Ching-Yung Lin,John Smith (2002). Real-time video surveillance for traffic monitoring using virtual line analysis.
R Cucchiara,M Piccardi,P Mello (2000). Image analysis and rule-based reasoning for a traffic monitoring system.
Osama Masoud,Nikolas Papanikolopoulos (2001). A Novel method for tracking and counting pedestrians in Real time using a single camera.
Paul Harini Veeraraghavan,Nikolas Schrater,Papanikolopoulos (2005). Switching Kalman filter-Based approach for Tracking and Event Detection at Traffic Intersection.
Berthold Horn,Brian Schunck (1981). Determining optical flow.

Download References

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. H.S. Mohana, G. Shivakumar, Aswatha Kumar. 1970. "Vehicle Counting and Classification Using Kalman Filter and Pixel Scanner Technique and its verification with Optical Flow Estimation". Global Journal of Computer Science and Technology GJCST Volume 10 (GJCST Volume 10 Issue 8).

More Citation Formats

Select Citation Style:

Download Citation

GJCST Volume 10 Issue 8

Explore Journals Explore Volume Read This Issue

Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Not Found

Submission ReceivedFebruary 13, 2010
Peer Review Double Blind
Handling Editor
Accepted March 2, 2010
Published March 15, 2010

Version of record

v1.2

Issue date

September 20, 2010

Language

English

Experiance in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

View in VR

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

View in 3D

Article Matrices

Total Score: 148

Country: Unknown

Subject: Global Journal of Computer Science and Technology

Authors: Dr. H.S. Mohana, Aswatha Kumar. M , G. Shivakumar (PhD/Dr. count: 1)

View Count (all-time): 189

Total Views (Real + Logic): 4962

Total Downloads (simulated): 334

Publish Date: 2010 03, Mon

Monthly Totals (Real + Logic):

Month 1: 36 views
Month 2: 39 views
Month 3: 25 views
Month 4: 36 views
Month 5: 64 views
Month 6: 52 views
Month 7: 40 views
Month 8: 48 views
Month 9: 51 views
Month 10: 38 views
Month 11: 40 views
Month 12: 17 views
Month 13: 28 views
Month 14: 25 views
Month 15: 32 views
Month 16: 21 views
Month 17: 25 views
Month 18: 31 views
Month 19: 34 views
Month 20: 32 views
Month 21: 45 views
Month 22: 19 views
Month 23: 21 views
Month 24: 24 views
Month 25: 17 views
Month 26: 43 views
Month 27: 35 views
Month 28: 21 views
Month 29: 37 views
Month 30: 30 views
Month 31: 22 views
Month 32: 18 views
Month 33: 20 views
Month 34: 22 views
Month 35: 24 views
Month 36: 38 views
Month 37: 33 views
Month 38: 29 views
Month 39: 40 views
Month 40: 37 views
Month 41: 23 views
Month 42: 29 views
Month 43: 27 views
Month 44: 11 views
Month 45: 36 views
Month 46: 43 views
Month 47: 38 views
Month 48: 43 views
Month 49: 42 views
Month 50: 19 views
Month 51: 36 views
Month 52: 12 views
Month 53: 36 views
Month 54: 30 views
Month 55: 18 views
Month 56: 23 views
Month 57: 40 views
Month 58: 23 views
Month 59: 19 views
Month 60: 33 views
Month 61: 16 views
Month 62: 30 views
Month 63: 29 views
Month 64: 48 views
Month 65: 42 views
Month 66: 35 views
Month 67: 35 views
Month 68: 21 views
Month 69: 44 views
Month 70: 48 views
Month 71: 32 views
Month 72: 50 views
Month 73: 34 views
Month 74: 28 views
Month 75: 39 views
Month 76: 37 views
Month 77: 42 views
Month 78: 16 views
Month 79: 29 views
Month 80: 48 views
Month 81: 23 views
Month 82: 41 views
Month 83: 42 views
Month 84: 40 views
Month 85: 24 views
Month 86: 35 views
Month 87: 32 views
Month 88: 29 views
Month 89: 38 views
Month 90: 22 views
Month 91: 25 views
Month 92: 30 views
Month 93: 13 views
Month 94: 26 views
Month 95: 36 views
Month 96: 30 views
Month 97: 13 views
Month 98: 27 views
Month 99: 17 views
Month 100: 30 views
Month 101: 27 views
Month 102: 27 views
Month 103: 46 views
Month 104: 28 views
Month 105: 31 views
Month 106: 15 views
Month 107: 39 views
Month 108: 34 views
Month 109: 32 views
Month 110: 18 views
Month 111: 35 views
Month 112: 42 views
Month 113: 28 views
Month 114: 16 views
Month 115: 34 views
Month 116: 28 views
Month 117: 32 views
Month 118: 33 views
Month 119: 20 views
Month 120: 33 views
Month 121: 35 views
Month 122: 24 views
Month 123: 29 views
Month 124: 32 views
Month 125: 33 views
Month 126: 30 views
Month 127: 19 views
Month 128: 43 views
Month 129: 20 views
Month 130: 36 views
Month 131: 26 views
Month 132: 32 views
Month 133: 13 views
Month 134: 24 views
Month 135: 18 views
Month 136: 37 views
Month 137: 10 views
Month 138: 21 views
Month 139: 27 views
Month 140: 28 views
Month 141: 18 views
Month 142: 29 views
Month 143: 27 views
Month 144: 18 views
Month 145: 29 views
Month 146: 20 views
Month 147: 29 views
Month 148: 38 views
Month 149: 17 views
Month 150: 31 views
Month 151: 20 views
Month 152: 31 views
Month 153: 28 views
Month 154: 18 views
Month 155: 28 views
Month 156: 17 views
Month 157: 29 views
Month 158: 20 views
Month 159: 35 views
Month 160: 40 views
Month 161: 35 views
Month 162: 26 views
Month 163: 40 views
Month 164: 38 views
Month 165: 21 views
Month 166: 35 views
Month 167: 34 views
Month 168: 23 views
Month 169: 27 views
Month 170: 34 views
Month 171: 33 views
Month 172: 27 views
Month 173: 31 views
Month 174: 21 views
Month 175: 49 views
Month 176: 16 views
Month 177: 19 views
Month 178: 37 views
Month 179: 31 views
Month 180: 33 views
Month 181: 35 views
Month 182: 18 views
Month 183: 40 views
Month 184: 17 views
Month 185: 42 views
Month 186: 28 views
Month 187: 27 views
Month 188: 34 views
Month 189: 28 views
Month 190: 30 views
Month 191: 39 views
Month 192: 26 views
Month 193: 46 views
Month 194: 17 views
Month 195: 38 views
Month 196: 29 views
Month 197: 55 views
Month 198: 37 views
Month 199: 30 views

Total Views: 5K

Total Downloads: 334

All Trends