Texture features for image classification and retrieval.

A License plate recognition (LPR) system can be divided into the following steps: preprocessing, plate region extraction, plate region thresholding, character segmentation, character recognition and post-processing. For step 2, a combination of color and shape information of plate is used and a satisfactory extraction result is achieved. For step 3, first channel is selected, then threshold is computed and finally the region is thresholded. For step 4, the character is segmented along vertical, horizontal direction and some tentative optimizations are applied. For step 5, minimum Euclidean distance based template matching is used. And for those confusing characters such as '8' & 'B' and '0' & 'D', a special processing is necessary. And for the final step, validity is checked by machine and manual. The experiment performed by program based on aforementioned algorithms indicates that our LPR system based on color image processing is quite quick and accurate.

Automatic license plate recognition system based on color image processing

The engineering of computer vision systems that meet application specific computational and accuracy requirements is crucial to the deployment of real-life computer vision systems. This paper illustrates how past work on a systematic engineering methodology for vision systems performance characterization can be used to develop a real-time people detection and zooming system to meet given application requirements. We illustrate that by judiciously choosing the system modules and performing a careful analysis of the influence of various tuning parameters on the system it is possible to: perform proper statistical inference, automatically set control parameters and quantify limits of a dual-camera real-time video surveillance system. The goal of the system is to continuously provide a high resolution zoomed-in image of a person's head at any location of the monitored area. An omni-directional camera video is processed to detect people and to precisely control a high resolution foveal camera, which has pan, tilt and zoom capabilities. The pan and tilt parameters of the foveal camera and its uncertainties are shown to be functions of the underlying geometry, lighting conditions, background color/contrast, relative position of the person with respect to both cameras as well as sensor noise and calibration errors. The uncertainty in the estimates is used to adaptively estimate the zoom parameter that guarantees with a user specified probability, /spl alpha/, that the detected person's face is contained and zoomed within the image.

Statistical modeling and performance characterization of a real-time dual camera surveillance system

A method of recognizing a handwritten word of cursive script comprising providing a template of previously classified words, and optically reading a handwritten word so as to form an image representation thereof comprising a bit map of pixels. The external pixel contour of the bit map is extracted and the vertical peak and minima pixel extrema on upper and lower zones respectively of this external contour are detected. Feature vectors of the vertical peak and minima pixel extrema are determined and compared to the template so as to generate a match between the handwritten word and a previously classified word. A method for classifying an image representation of a handwritten word of cursive script is also provided. Also provided is an apparatus for recognizing a handwritten word of cursive script. This apparatus comprises a template of previously classified words, a reader for optically reading a handwritten word, and a controller being linked thereto for generating a match between the handwritten word and the previously classified words. Two algorithms are provided for respectively the skew and slant of a word image.

Handwritten word recognition based on geometric decomposition

A robust approach for extracting car license plate from images with complex background and relatively poor quality is presented. The approach focuses on dealing with images taken under weak lighting condition. The proposed method is divided into two steps: 1) searching candidate areas from the input image using gradient information, and 2) determining the plate area among the candidates and adjusting the boundary of the area by introducing a plate template. A set of experiments has been performed to prove the robustness and accuracy of the approach. For many images collected from a large underground parking place the result shows that 90% of them are correctly segmented.

A robust license-plate extraction method under complex image conditions

2D Gaussian blur operations are used in many image processing applications. The execution times of these operations can be rather long, especially where large kernels are involved. Proper use of two properties of Gaussian blurs can help to reduce these long execution times: (1) Large kernels can be decomposed into the sequential application of small kernels. (2) Gaussian blurs are separable into row and column operations. This paper makes use of both of these characteristics and adds a third one: (3) The row and column operations can be formulated as finite-state machines to produce highly efficient code and, for multi-step decompositions, eliminate writing to intermediate images. This paper shows the FSM formulation of the Gaussian blur for the general case and provides examples. Speed comparisons between various implementations are provided for some of the examples. The emphasis is on software implementations, but implementations in pipelined hardware are also discussed. Straightforward extensions of these concepts to 3- and higher-dimensional image processing are also presented. Implementation techniques for DOG (Difference-of-Gaussian filters) are also provided.

Efficient algorithm for Gaussian blur using finite-state machines

Recognition of license plate images is the topic of the paper. The major issue in this problem is the accurate extraction of the license plate string from varying backgrounds. The images are also characterized by non-uniform illumination. Recognition of the string is fairly straightforward, if the extraction process has been correctly designed. The authors discuss three different approaches to extraction and their study revealed that fusion of gray scale morphology and homomorphic processing yielded accurate extraction of the string. Recognition studies with 700 images captured during day and night times indicated an overall acceptance rate of 80% or higher with less than 1% confusion is achievable. Results obtained from a more exhaustive study that is currently in progress are presented.

Recognition of license plate images: issues and perspectives

The earlier papers on SKIPSM (Separated-Kernel Image Processing using finite State Machines) concentrated mainly on implementations using pipelined hardware. Because of the potential for significant speed increases, the technique has even more to offer for software implementations. However, the gigantic structuring elements (e.g., 51x51 in one pass) readily available in binary morphology using SKIPSM are not practical in grey-level morphology. Nevertheless, useful structuring element sizes can be achieved. This paper describes two such applications: dilation with a 7x7 square and a 7x7 octagon. Previous 2-D SKIPSM implementations had one row machine and one column machine. Two of the implementations described here follow this pattern, but the other has four machines: row, column, and the two 45-degree diagonals. In operation, all of these are one-pass algorithms: The next pixel is fetched from the input device, the two (or four) machines are updated in turn, and the resulting output pixel is written to the output device. All neighborhood information needed for processing is encoded in the state vectors of the finite-state machines. Therefore, no intermediate image stores are needed. Furthermore, even the input and output image stores can be eliminated if the image processor can keep up with the input pixel rate. Comparisons are provided between these finite-state-machine implementations and conventional implementation of the 2-step and 4-step decompositions, all based on the same structuring elements.

Software implementation of 2-D grey-level dilation using SKIPSM

A vision system to gauge two types of automotive parts has been developed. One of the part types is a power steering connector in which the depth and width of the groove, and the distance between the start of the groove and the end of the power steering line are gauged. For the second type of part, a crimped connector attached to a brake hose, measurements of interest are the two diameters of the crimp and the bell length where the hose is inserted into the connector. A standard video camera is used to acquire the image of a back-illuminated image of the part which is digitized and captured with a frame grabber. The basic hardware to accomplish the gauging tasks consists of a standard video camera, light source, frame grabber and industrial personal computer. In order to minimize hardware costs, a standard 50 mm C-mount camera lens and extension tube was used with the video camera. Consideration had been made to use more expensive telecentric optics so that parts placement would not cause a change in magnification with a resulting loss of accuracy. With the 50 mm lens, however, magnification effects were lessened due to the greater standoff distance between camera and part. For image acquisition, a low-cost PCI-bus frame grabber-card was chosen. With this type of card, high-speed video capture is possible due to the very wide bandwidth of the PCI bus. Combined with a Pentium-based PC, rapid image acquisition and analysis can be performed so that every part can be gauged at full production rates. Since the gauging rate exceeds the production rate by a significant factor, a single computer and frame grabber with camera multiplexer can process data in real time from up to four measurement stations simultaneously.

John W. V. Miller

Papers

Efficient algorithm for Gaussian blur using finite-state machines

Recognition of license plate images: issues and perspectives

Software implementation of 2-D grey-level dilation using SKIPSM

Very low cost in-process gauging system

Machine Vision Systems for Inspection and Metrology VII