Hough Transform Research Papers - Academia.edu (original) (raw)

Visual impairment and blindness caused by infectious diseases has been greatly reduced, but increasing numbers of people are at risk of age-related visual impairment. Visual information is the basis for most navigational tasks, so... more

Visual impairment and blindness caused by infectious diseases has been greatly reduced, but increasing numbers of people are at risk of age-related visual impairment. Visual information is the basis for most navigational tasks, so visually impaired individuals are at disadvantage because appropriate information about the surrounding environment is not available. With the recent advances in inclusive technology it is possible to extend the support given to people with visual impairment during their mobility. In this context we propose a system, named SmartVision, whose global objective is to give blind users the ability to move around in unfamiliar environments, whether indoor or outdoor, through a user friendly interface. This paper is focused mainly in the development of the computer vision module of the SmartVision system.

We present an efficient Hough transform for automatic detection of cylinders in point clouds. As cylinders are one of the most frequently used primitives for industrial design, automatic and robust methods for their detection and fitting... more

We present an efficient Hough transform for automatic detection of cylinders in point clouds. As cylinders are one of the most frequently used primitives for industrial design, automatic and robust methods for their detection and fitting are essential for reverse engineering from point clouds. The current methods employ automatic segmentation followed by geometric fitting, which requires a lot of manual interaction during modelling. Although Hough transform can be used for automatic detection of cylinders, the required 5D Hough space has a prohibitively high time and space complexity for most practical applications. We address this problem in this paper and present a sequential Hough transform for automatic detection of cylinders in point clouds. Our algorithm consists of two sequential steps of low dimensional Hough trans- forms. The first step, called Orientation Estimation, uses the Gaussian sphere of the input data and performs a 2D Hough Transform for finding strong hypotheses ...

Technological intelligence is a highly sought after commodity even in traffic-based systems. These intelligent systems do not only help in traffic monitoring but also in commuter safety, law enforcement and commercial applications. In... more

Technological intelligence is a highly sought after commodity even in traffic-based systems. These intelligent systems do not only help in traffic monitoring but also in commuter safety, law enforcement and commercial applications. In this paper, a license plate localization and recognition system for vehicles in Malaysia is proposed. This system is developed based on digital images and can be easily

A multi-font, multi-size Optical Character Recognizer (OCR) of Tamil Script is developed. The input image to the system is binary and is assumed to contain only text. The skew angle of the document is estimated using a combination of... more

A multi-font, multi-size Optical Character Recognizer (OCR) of Tamil Script is developed. The input image to the system is binary and is assumed to contain only text. The skew angle of the document is estimated using a combination of Hough transform and Principal Component Analysis. A multi-rate-signal-processing based algorithm is devised to achieve distortion-free rotation of the binary image during skew correction. Text segmentation is noise-tolerant. The statistics of the line height and the character gap are used to segment the text lines and the words. The images of the words are subjected to morphological closing followed by connected component-based segmentation to separate out the individual symbols. Each segmented symbol is resized to a pre-fixed size and thinned before it is fed to the classifier. A three-level, tree-structured classifier for Tamil script is designed. The net classification accuracy is 99.0%.

This work is a preliminary step in the development of a computer system for automatic identification of weapons with the aid of fired cartridge cases. We study the particular characteristics that can be present on the bottom of the... more

This work is a preliminary step in the development of a computer system for automatic identification of weapons with the aid of fired cartridge cases. We study the particular characteristics that can be present on the bottom of the cartridge head, which are helpful for automatic identification of the corresponding weapon, and we discuss how to extract and use those features.

Line detection is a very basic, yet important problem in image processing. It is an approach based on whether sets of pixels lie on curves of a specified shape. Once detected, these curves form the edges of interest. Most of the shape... more

Line detection is a very basic, yet important problem in image processing. It is an approach based on whether sets of pixels lie on curves of a specified shape. Once detected, these curves form the edges of interest. Most of the shape information of an image is enclosed in edges. So first detect these edges in an image and by using these filters and then by enhancing those areas of image. Which contains edges, sharpness of the image will increase and image will become clearer. However the output from an edge detector is still an image described by its pixels. If lines, ellipses and so forth could be defined by their characteristic equations, the amount of data would be reduced even more. Line detection is an algorithm that takes a collection of an edge points and finds all the lines on which these edge points lie. The most popular line detectors are the Hough transform and convolution based techniques. While edges (i.e. boundaries between regions with relatively distinct gray levels) are by far the most common type of discontinuity in an image, instances of thin lines in an image occur frequently enough that it is useful to have a separate mechanism for detecting them. Here present a convolution based technique which produces an image description of the thin lines in an input image. Note that the Hough transform can be used to detect lines; however, in that case, the output is a parametric description of the lines in an image.

This paper describes a novel Driver Assistant System based on real-time video to track lanes and road signs with minimal hardware and software requirements. The proposed system was designed to use low cost cameras and processing power of... more

This paper describes a novel Driver Assistant System based on real-time video to track lanes and road signs with minimal hardware and software requirements. The proposed system was designed to use low cost cameras and processing power of an on-board commodity laptop. The system model was developed using MATLAB®/Simulink blocksets. This was later converted into an optimized compiled code using the built-in code generation features for the Pentium and AMD processors. The lane tracking algorithm based on Hough Transform was implemented as embedded MATLAB® code. The signboards were detected by Blob Analysis Based Template Matching. Sum of Absolute Differences (SAD) as well as Scale Invariant Feature Transform (SIFT) followed by RANdom SAmple Consensus (RANSAC) based template matching methods. The above were implemented and compared for their performance. The developed system was tested on different drives varying from a high speed drive on a high way to a low speed drive on the city roa...

The Hough transform provides a robust technique for skew detection in document images, but suffers from high time complexity which becomes prohibitive for detecting skew in large documents. Analysis of time complexity on various stages of... more

The Hough transform provides a robust technique for skew detection in document images, but suffers from high time complexity which becomes prohibitive for detecting skew in large documents. Analysis of time complexity on various stages of skew detection process is carried out in this paper. A complete skew detection and correction process is divided into three parts: a preprocessing stage using a simplified form of block adjacency graph (BAG), voting process using the Hough transform and de-skewing the image using rotation. Skew correction phase, which is hitherto a neglected area, is analysed for the quality of de-skewed images with respect to the type of rotation. Fast algorithms for all the three stages are presented and exhaustive analysis on time complexity is conducted. It is shown that the overall time taken for the whole process is less than one second even for very large documents. It is also observed that time taken in rotation is as significant as in skew detection which is reduced with the help of fast algorithms using integer operations. While the BAG algorithm is found to be effective for documents with Roman script, it does not provide satisfactory results for Indian scripts where headline is a part of a script.

Searching for the parking space is a time-consuming task while visiting for shopping or unknown cities. Real-time parking management gets benefited for the development of the smart city and also reduces time for finding the parking place.... more

Searching for the parking space is a time-consuming task while visiting for shopping or unknown cities. Real-time parking management gets benefited for the development of the smart city and also reduces time for finding the parking place. In this chapter, different two types of modules for car parking are simulated using a combination of Hough transform, edge detection, and color enhancement method. Different car parking modules are circular shape-based: (i) parallel parking with a different radius and (ii) angle parking with the same radius. Real-time video is captured using an android smartphone with an IP camera. The proposed research work can enhance the solution for real-time parking solution in big malls and theater. Limitation and future scope of this will give motivation toward research work on an intelligent transportation system (ITS) development in India. For small-scale version here, we have used toy cars and bus with a different color for parking modules.

This paper describes a computer vision based automatic scoring system of shooting targets. The system estimates scoring with a professional tournament precision, but is dedicated to amateur shooters and can work with photos taken by... more

This paper describes a computer vision based automatic scoring system of shooting targets. The system estimates scoring with a professional tournament precision, but is dedicated to amateur shooters and can work with photos taken by amateur cameras and mobile devices.
The automatic scoring issue is divided into three problems: a target detection, a holes detection, and a hole analysis. The target is detected on the base of a bull-eye localization. The holes detection bases on the Hough transformation. The holes analysis localizes a position of hole's center. The position relative to detected scoring sections is a base for scoring.
The proposed algorithm detects holes with 99 percent accuracy. An elimination of false positives results reduces the level of accepted holes to 92 percents.
The average error for the automatic score estimation is 0.05 points. The estimation error for over 91 percent holes is lesser than a tournament-scoring threshold.

Now a days computer aided design and diagnosis is very popular. Most of the diseases screening and detection is performed with the help of a computer. Diabetic retinopathy is one of the diabetic eye diseases found in the patients who have... more

Now a days computer aided design and diagnosis is very popular. Most of the diseases screening and detection is performed with the help of a computer. Diabetic retinopathy is one of the diabetic eye diseases found in the patients who have diabetic in last 20-30 years. The main objective of this work is to effectively found diabetic retinopathy those who have diabetic by using Hough transform and bottom hat transform. Selection of the needed region and extract the decided feature is very important in CAD. Hough transform is one of the best method for feature extraction. It follows voting procedure for feature extraction. The purpose of the technique is to find imperfect instances of objects within a certain class of shapes.

Hough transform is a general technique for identifying the locations and orientations of certain types of features in a digital image and used to isolate features of a particular shape within an image. Because it requires that the desired... more

Hough transform is a general technique for identifying the locations and orientations of certain types of features in a digital image and used to isolate features of a particular shape within an image. Because it requires that the desired features are specified in some parametric form, classical Hough transform is the most commonly used for the detection of regular curves

Cell enumeration in peripheral blood smears and cell are widely applied in biological and pathological practice. Not every area in the smear is appropriate for enumeration due to severe cell clumping or sparseness arising from smear... more

Cell enumeration in peripheral blood smears and cell are widely applied in biological and pathological practice. Not every area in the smear is appropriate for enumeration due to severe cell clumping or sparseness arising from smear preparation. The automatic selection of good areas for cell enumeration can reduce manual labor and provide objective and consistent results. However, this has been infrequently studied and it is often difficult to count the exact number of cells in the clumps. To select good areas, we do not have to do this. Instead, we measure the goodness of such areas in terms of the degree of cell spread and the degree of clumping. The later is defined based on the distances and linking strengths of local voting peaks generated in the accumulator space after multi-scale circular Hough transforms. Support vector machines are then applied to classify the image areas into good or non-good classes. We have validated our method over 4500 testing cell images and achieved 89% sensitivity and 87% specificity.

Lane detection and tracking is one of the key features of advanced driver assistance system. Lane detection is finding the white markings on a dark road. Lane tracking use the previously detected lane markers and adjusts itself according... more

Lane detection and tracking is one of the key features of advanced driver assistance system. Lane detection is finding the white markings on a dark road. Lane tracking use the previously detected lane markers and adjusts itself according to the motion model. In this paper, review of lane detection and tracking algorithms developed in the last decade is discussed. Several modalities are considered for lane detection which include vision, LIDAR, vehicle odometry information, information from global positioning system and digital maps. The lane detection and tracking is one of the challenging problems in computer vision. Different vision based lane detection techniques are explained in the paper. The performance of different lane detection and tracking algorithms is also compared and studied.

A large number of methods for circle detection have been studied in the last years for several image processing applications. The context application considered in this work is the soccer game. In the sequences of soccer images it is very... more

A large number of methods for circle detection have been studied in the last years for several image processing applications. The context application considered in this work is the soccer game. In the sequences of soccer images it is very important to identify the ball in order to verify the goal event. This domain is a challenging one as a great number of problems have to be faced, such as occlusions, shadows, objects similar to the ball, real-time processing and so on. In this work a visual framework trying to solve the above-stated problems, mainly considering real-time computational aspects, has been developed. The ball detection algorithm has to be very simple in terms of time processing and also has to be efficient in terms of false positive rate. Our framework consists of two sequential steps for solving the ball recognition problem: the first step uses a modified version of the directional circle Hough transform to detect the region of the image that is the best candidate to contain the ball; in the second step a neural classifier is applied on the selected region to confirm if the ball has been properly detected or a false positive has been found. Some tricks like background subtraction and ball tracking have been applied in order to maintain the search of the ball only in limited areas of the image. Different light conditions have been considered as they introduce strong modifications on the appearance of the ball in the image: when the image sequences are taken with natural light, as the light source is strictly directional, the ball, due to self-shades, appears as a spherical cap; this case has been taken in account and the search of the ball has been modified in order to manage this situation. A large number of experiments have been carried out showing that the proposed method obtains a high detection score.

The number of red blood cells contributes more to clinical diagnosis with respect to blood diseases. The aim of this research is to produce a computer vision system that can detect and estimate the number of red blood cells in the blood... more

The number of red blood cells contributes more to clinical diagnosis with respect to blood diseases. The aim of this research is to produce a computer vision system that can detect and estimate the number of red blood cells in the blood sample image. Morphological is a very powerful tool in image processing, and it is been used to segment and extract the red blood cells from the background and other cells. The algorithm used features such as shape of red blood cells for counting process, and Hough transform is introduced in this process. The result presented here is based on images with normal blood cells. The tested data consists of 10 samples and produced the accurate estimation rate closest to 96% from manual counting.

This paper focuses on implementation of a speedy Hough Transform (HT) which considers the memory constraints of the system. Because of high memory demand, small systems (DSPs, tiny robots) cannot realize efficient implementation of HT.... more

This paper focuses on implementation of a speedy Hough Transform (HT) which considers the memory constraints of the system. Because of high memory demand, small systems (DSPs, tiny robots) cannot realize efficient implementation of HT. Keeping this scenario in mind, the paper discusses an effective and memory-efficient method of employing the HT for extraction of line features from a gray scale image. We demonstrate the use of a circular buffer for extraction of image edge pixels and store the edge image in a manner that is different from the conventional way. Approximation of the two dimensional Hough Space by a one dimensional array is also discussed. The experimental results reveal that the proposed algorithm produces better results, on small and large systems, at a rapid pace and is economical in terms of memory usage.

This paper proposes a new idea for grading multiple-choice test which is based on a camera with reliability and efficiency. The bounds of the answer sheet image captured by the camera is first allocated using Hough transform and then... more

This paper proposes a new idea for grading multiple-choice test which is based on a camera with reliability and efficiency. The bounds of the answer sheet image captured by the camera is first allocated using Hough transform and then skew-corrected into the proper orientation, followed by the normalization to a given size. Next, the tick mark corresponding to the answer for each question can be recognized by allocation of the mask which wraps the answer area. The experimental results showed that the proposed system has achieved significant improvement in performance in terms of accuracy, reliability, and elapsed time compared with those of the conventional optical mark recognition (OMR) systems. The proposed system also demonstrated that it can also achieve high accuracy of 99.7% while using non-transoptic answer sheet paper with lower cost.