This paper presents a novel and real-time system for interaction with an application or video game via hand gestures. Our system includes detecting and tracking bare hand in cluttered background using skin detection and hand posture contour comparison algorithm after face subtraction, recognizing hand gestures via bag-of-features and multiclass support vector machine (SVM) and building a grammar that generates gesture commands to control an application. In the training stage, after extracting the keypoints for every training image using the scale invariance feature transform (SIFT), a vector quantization technique will map keypoints from every training image into a unified dimensional histogram vector (bag-of-words) after K-means clustering. This histogram is treated as an input vector for a multiclass SVM to build the training classifier. In the testing stage, for every frame captured from a webcam, the hand is detected using our algorithm, then, the keypoints are extracted for every small image that contains the detected hand gesture only and fed into the cluster model to map them into a bag-of-words vector, which is finally fed into the multiclass SVM training classifier to recognize the hand gesture.

Real-Time Hand Gesture Detection and Recognition Using Bag-of-Features and Support Vector Machine Techniques

This paper discussed on automatic parking system
and electronic parking fee collection based on vehicle number
plate recognition. The aim of this research is to develop and
implement an automatic parking system that will increase
convenience and security of the public parking lot as well as
collecting parking fee without hassles of using magnetic card.
The auto parking system will able to have less interaction of
humans and use no magnetic card and its devices. In additions
to that, it has parking guidance system that can show and guide
user towards a parking space. The system used image
processing of recognizing number plates for operation of
parking and billing system. Overall, the systems run with
pre-programmed controller to make minimum human
involvement in parking system and ensure access control in
restricted places. This paper presents algorithm technology
based method for license plate extraction from car images
followed by the segmentation of characters and reorganization
and also develop electronics parking fee collection system based
on number plate information.

/pdf/automatic-parking-management-system-and-parking-fee-4ukv80tgu7.pdf

Automatic Parking Management System and Parking Fee Collection Based on Number Plate Recognition

This paper presents a real time system, which includes detecting and tracking bare hand in cluttered background using skin detection and hand postures contours comparison algorithm after face subtraction, and recognizing hand gestures using Principle Components Analysis (PCA). In the training stage, a set of hand postures images with different scales, rotation and lighting conditions are trained. Then, the most eigenvectors of training images are determined, and the training weights are calculated by projecting each training image onto the most eigenvectors. In the testing stage, for every frame captured from a webcam, the hand gesture is detected using our algorithm, then the small image that contains the detected hand gesture is projected onto the most eigenvectors of training images to form its test weights. Finally, the minimum Euclidean distance is determined between the test weights and the training weights of each training image to recognize the hand gesture.

Hand gesture detection and recognition using principal component analysis

A skin detection approach based on the Dempster--Shafer theory of evidence

Automatic License Plate Identification (ALPI) has many applications in traffic systems (highway electronic toll collection, red light violation enforcement, border and customs checkpoints etc.). This paper presents Automatic Number Plate Extraction and Character Segmentation for Indian vehicles. In India, number plate models are not followed strictly. Characters on plate are in different Indian languages, as well as in English. Due to variations in the representation of number plates, vehicle number plate extraction and character segmentation is difficult. We work on plates that contain English characters. The proposed algorithm consists of three major parts: Preprocessing of Image, Extraction of plate region and Segmentation of characters. For preprocessing of the image, histogram equalization has been applied. For extracting the Plate region, edge detection algorithm and various morphological operations are used. Character segmentation is done by using connected component and bounding box method. The accuracy of our algorithm for license plate extraction is 91.02% and for segmentation is 88.46%.

Indian vehicle license plate extraction and segment ation

This paper presents a comprehensive study of the pixel-based skin color detection techniques. Two main issues of the skin detection are the selection of the best color space and skin color pixel classification algorithm. A large set of XM2VTS face database is used to examine whether the selection of color space can enhance the compactness of the skin class and discriminability between skin and non-skin class in thirteen color spaces and six different skin color pixel classification algorithms. The results show that 1) the selection of the color space can improve the skin classification performance 2) the segmentation performance degrades only when chrominance information is used for classification 3) Bayesian classifier is found to perform better as compared to other classification algorithms. Piecewise linear decision boundary classifier algorithm outperforms all the other skin classification algorithms when it is used for images with good illumination conditions.

https://www2.computer.org/portal/web/csdl/doi/10.1109/ICCIMA.2007.208

Skin Detection Using Color Pixel Classification with Application to Face Detection: A Comparative Study

Locating the car license plate in an image a car is an important step in car license plate recognition/identification applications. This problem poses many challenges like location of license plate from images taken in poor illumination and bad weather condition; plates that are partly obscured by dirt and images that have low contrast. This paper presents a morphology based method for license plate extraction from car images followed by the segmentation of characters and reorganization. This algorithm uses morphological operations on the preprocessed, edge images of the vehicles. Characteristic features such as license plate width and height, character height and spacing are considered for defining structural elements for morphological operations. The recognition of the contents of the license plate is performed using cross correlation followed by neural network. The experimental results with a reasonably large set of car images are very encouraging.

C.N.K. Babu

Papers

Skin Detection Using Color Pixel Classification with Application to Face Detection: A Comparative Study

A license plate localization using morphology and recognition