Kaushik Deb

Vehicle License Plate Detection Method Based on Sliding Concentric Windows and Histogram

Detecting the region of a license plate is the key component of the vehicle license plate recognition (VLPR) system. A new method is adopted in this paper to analyze road images which often contain vehicles and extract LP from natural properties by finding vertical and horizontal edges from vehicle region. The proposed vehicle license plate detection (VLPD) method consists of three main stages: (1) a novel adaptive image segmentation technique named as sliding concentric windows (SCWs) used for detecting candidate region; (2) color verification for candidate region by using HSI color model on the basis of using hue and intensity in HSI color model verifying green and yellow LP and white LP, respectively; and (3) finally, decomposing candidate region which contains predetermined LP alphanumeric character by using position histogram to verify and detect vehicle license plate (VLP) region. In the proposed method, input vehicle images are commuted into grey images. Then the candidate regions are found by sliding concentric windows. We detect VLP region which contains predetermined LP color by using HSI color model and LP alphanumeric character by using position histogram. Experimental results show that the proposed method is very effective in coping with different conditions such as poor illumination, varied distances from the vehicle and varied weather.

Combined DWT-DCT based digital image watermarking technique for copyright protection

A combined DWT and DCT based watermarking technique with low frequency watermarking with weighted correction is proposed. DWT has excellent spatial localization, frequency spread and multi-resolution characteristics, which are similar to the theoretical models of the human visual system (HVS). DCT based watermarking techniques offer compression while DWT based watermarking techniques offer scalability. These desirable properties are used in this combined watermarking technique. In the proposed method watermark bits are embedded in the low frequency band of each DCT block of selected DWT sub-band. The weighted correction is also used to improve the imperceptibility. The extracting procedure reverses the embedding operations without the reference of the original image. Compared with the similar approach by DCT based approach and DWT based approach, the experimental results show that the proposed algorithm apparently preserves superior image quality and robustness under various attacks such as JPEG compression, cropping, sharping, contrast adjustments and so on.

HSI color based vehicle license plate detection

Vehicle license plate recognition (VLPR) is one of the most important topics of using computer vision and pattern recognition in intelligent transportation systems. In order to recognize a license plate (LP) expeditiously, the location of the LP in most cases, must be detected in the initial step. For this reason, detecting the exact and perfect location of a LP from a vehicle image is considered to be the most important and crucial step of a VLPR system, which greatly affects the recognition process and directly influences the accuracy and speed of entire system. In this paper a HSI color based license plate detection method is proposed. In this method, (a) HSI color model is used for detecting candidate regions and (b) vehicle license plate (VLP) regions are verified and detected by using position histogram. In the proposed method, input vehicle images are converted into HSI color images. Then the candidate regions are found by HSI color model on the basis of using hue, saturation and/or intensity. These candidate regions may include LP regions; geometrical properties of LP are then used for classification. Finally, VLP regions containing predetermined LP alphanumeric character are verified and detected by using position histogram. The proposed method is very effective in coping with different conditions such as poor illumination and varied weather comparing with traditional approaches. Experimental results show that the distance from the vehicle varied according to the camera setup.

Parallelogram and Histogram based Vehicle License Plate Detection

This paper describes a new approach to analyze road images which often contain vehicles and extract license plate (LP) from natural properties by finding vertical and horizontal edges from vehicle region. The proposed technique consists of three main modules: (a) segmentation technique named as sliding concentric windows (SCW) on the basis of a novel adaptive image for detecting candidate region, (b) refining by using HSI color model on the basis of using hue and intensity in HSI color model verifying green and yellow LP and white LP, respectively and (c) finally, verify and detect VLP region which contains predetermined LP alphanumeric character by using position histogram. In the proposed method, input vehicle images are converted into gray images. After then the candidate regions are found by sliding concentric windows. We detect vehicle license plates (VLP) region which contains predetermined LP color by using HSI color model and LP alphanumeric character by using position histogram. Experimental results show that the proposed method is very effective in coping with different conditions such as poor illumination and varied weather. Experimental results also show that the distance from the vehicle varied according to the camera setup.

A VEHICLE LICENSE PLATE DETECTION METHOD FOR INTELLIGENT TRANSPORTATION SYSTEM APPLICATIONS

Detecting license plates is crucial and inevitable in the vehicle license plate recognition system. In this article, a Hue-Saturation-Intensity (HSI) color model is adopted to select automatically statistical threshold value for detecting candidate regions. The focus of this article is on the implementation of a new method to detect candidate regions when vehicle bodies and license plates (LP) have similar color. The proposed method is able to deal with candidate regions under independent orientation and scale of the plate. For the decomposing candidate regions, predetermined LP alphanumeric characters are used by position histogram to verify and detect vehicle LP regions. Various LP images were used with a variety of conditions to test the proposed method and results proved its effectiveness.

Fast HDR image generation technique based on exposure blending

In the proposed work a method for generating HDR images based on exposure blending is described. Using three differently exposed images a single image with recovered details in shadows and highlights is generated. Input images are analyzed to locate over and underexposed regions based on pixels intensity. Local contrast of input images is also considered in order to generate the output image with correct color transactions between differently exposed areas. Then images are merged using blending function. The proposed method requires a single pass thru the image to generate the result, which allows to process one image for less than 100 milliseconds. The proposed method requires no information about camera or shutting conditions, such as shutter speed or aperture size.

An Efficient Method of Vehicle License Plate Detection Based on HSI Color Model and Histogram

Detecting license plate (LP) is a crucial and inevitable component of the vehicle license plate recognition (VLPR) system. In this paper to select automatically statistical threshold value in HSI color model is proposed. The proposed vehicle license plate detection (VLPD) method consists of two main stages. Initially, HSI color model is adopted for detecting candidate regions. According to different colored LP, these candidate regions may include LP regions; geometrical properties of LP are then used for classification. The proposed method is able to deal with candidate regions under independent orientation and scale of the plate. Finally, the decomposition of candidate regions contains predetermined LP alphanumeric characters by using position in the histogram to verify and detect vehicle license plate (VLP) region. Experimental results show that the proposed method is very effective in coping with different images under the variety of conditions such as complex scenes, illumination changing, distances and varied weather etc.

Moment invariants based object recognition for different pose and appearances in real scenes

Object recognition in real scenes is a central problem in computer vision. In this paper we propose a new approach for shape based recognition of objects in real scenes. This approach uses moment invariants for identification of shape features. Moment Invariants are functions of central moments. They are invariant against linear transformations such as rotation, translation and scaling. Therefore, their integration provides recognition of objects in real scenes with different pose and appearances. In this way, the proposed approach does not only provide invariant object recognition, but also capable of dealing with challenges like variation in pose and appearances. We have used linear support vector machine (SVM) for classification of object and non-object data. With qualitative and quantitative experimental evaluation on standard INRIA Pedestrian dataset, we have compared performance of the proposed method with other state of the art shape feature descriptors based object recognition methods and demonstrated better performance over them.

Bangladeshi Vehicle License Plate Detection method based on HSI color model and geometrical properties

Bangladeshi Vehicle License Plate Detection (BVLPD) plays an important and inevitable role in Vehicle License Plate Recognition (VLPR) system. The most challenging part of this method is to detect the region of the license plate from the vehicle image. In this paper, we propose an algorithm for analyzing the vehicle image to extract the LP position in the image of the vehicle. Initially, HSI color model is adopted to select a threshold for detecting candidate regions and then different geometrical properties of LP such as area, bounding box, aspect ratio are used to determine whether the candidate regions contain LP or not. Finally the candidate region is verified by intensity histogram. The proposed method is able to deal with candidate regions under different scale of the plate. In the experiment more than 100 images are used which are taken under different conditions such as uneven illumination, complex scenes, varied weather and varied distances from the vehicle to camera. The overall rate of success of the license plate detection algorithm is 85%.

Vehicle license plate detection algorithm based on color space and geometrical properties

In this paper, an algorithm for vehicle license plate detection (VLPD) is proposed, to select automatically statistical threshold value in HSI color space. The proposed VLPD algorithm consists of two main stages. Initially, HSI color space is adopted for detecting candidate regions. According to different colored LP, these candidate regions may include LP regions; geometrical properties of LP are then used for classification. The proposed method is able to deal with candidate regions under independent orientation and scale of the plate. Finally, the decomposition of candidate regions contains predetermined LP alphanumeric characters by using position in the histogram to verify and detect vehicle license plate (VLP) region. In experiment more than 150 images were used, they were taken from the variety of conditions such as complex scenes, illumination changing, distances and varied weather etc. Under these conditions, success of LP detection has reached to more than 94%.