Abstract: The present invention discloses a method of evaluating image quality taken in an actual scene, the method comprising: providing a test chart placed in an actual scene, said test chart comprising a plurality of positioning patterns and a plurality of quality test patterns; capturing an image of the test chart in the actual scene; searching the plurality of positioning patterns in the image of the test chart to locate the orientation of the image of the test chart; and identifying the plurality of quality test patterns in the located image of the test chart and evaluating the image quality of the plurality of quality test patterns.

Abstract: The present invention discloses a method of evaluating image quality taken in an actual scene, the method comprising: providing a test chart placed in an actual scene, said test chart comprising a plurality of positioning patterns and a plurality of quality test patterns; capturing an image of the test chart in the actual scene; searching the plurality of positioning patterns in the image of the test chart to locate the orientation of the image of the test chart; and identifying the plurality of quality test patterns in the located image of the test chart and evaluating the image quality of the plurality of quality test patterns.

Abstract: A method for face recognition based on online learning by calculating a similarity between each of the face images captured in a specific environment and a target face image so as to form a distribution of the similarities of the face images with respect to the target face image, wherein a similarity threshold with respect to the first target face image is determined according to a predefined rule and the distribution of the similarities, wherein the similarity threshold is used for subsequent selection of a face image captured in the specific environment and having a similarity greater than said similarity threshold with respect to the target face image.

Abstract: Described herein are a system and a method for abnormal behavior detection using automatic classification of multiple features. Features from various sources, including those extracted from camera input through digital image analysis, are used as input to machine learning algorithms. These algorithms group the features and produce models of normal and abnormal behaviors. Outlying behaviors, such as those identified by their lower frequency, are deemed abnormal. Human supervision may optionally be employed to ensure the accuracy of the models. Once created, these models can be used to automatically classify features as normal or abnormal. This invention is suitable for use in the automatic detection of abnormal traffic behavior such as running of red lights, driving in the wrong lane, or driving against traffic regulations.

Abstract: The invention discloses a correction method and system for object linking in video sequences that are captured by a multiple camera surveillance video system. The invention allows a user to select a specific object to track and for trace correction through an interactive user platform. The interactive user platform shows a video sequence captured by the user-selected camera at the selected time; lists of previous and post video sequences related to the user-selected object or video sequences, and lists of object linking results before and after the selected time. The user refers to the linking results, shown in lists of object linking results before and after the selected time to select one of objects for correction in selected frame of selected video sequence. The selection directs the proposed system to correct the trace of the specific object to track. Henceforth, the correct linking results can be automatically generated.

Abstract: The invention discloses a correction method and system for object linking in video sequences that are captured by a multiple camera surveillance video system. The invention allows a user to select a specific object to track and for trace correction through an interactive user platform. The interactive user platform shows a video sequence captured by the user-selected camera at the selected time; lists of previous and post video sequences related to the user-selected object or video sequences, and lists of object linking results before and after the selected time. The user refers to the linking results, shown in lists of object linking results before and after the selected time to select one of objects for correction in selected frame of selected video sequence. The selection directs the proposed system to correct the trace of the specific object to track. Henceforth, the correct linking results can be automatically generated.

Abstract: Disclosed herein are a system and method for the automatic detection of traffic and parking violations. Camera input is digitally analyzed for vehicle type and location. This information is then processed against local traffic and parking regulations to detect violations. Detectable driving offenses include, but are not limited to: no scooters, buses only, and scooters only lane violations. Detectable parking offenses include, but are not limited to: parking or loitering in bus stops, parking next to fire hydrants, and parking in no-parking zones. Camera input, detected vehicle information, and violations can be stored for later search and retrieval. The system may be configured to signal the authorities or other automated analysis systems about specific violations. When coupled with automatic license plate recognition, vehicles may be automatically matched against a registration database and reported or ticketed.

Abstract: Described herein are a system and a method for abnormal behavior detection using automatic classification of multiple features. Features from various sources, including those extracted from camera input through digital image analysis, are used as input to machine learning algorithms. These algorithms group the features and produce models of normal and abnormal behaviors. Outlying behaviors, such as those identified by their lower frequency, are deemed abnormal. Human supervision may optionally be employed to ensure the accuracy of the models. Once created, these models can be used to automatically classify features as normal or abnormal. This invention is suitable for use in the automatic detection of abnormal traffic behavior such as running of red lights, driving in the wrong lane, or driving against traffic regulations.

Abstract: A string extraction method for an image based on multiple stroke width patterns matching is provided. The string extraction method includes matching each possible stroke width pattern with an input image for obtaining the similarities between the width patterns and each pixel, wherein the integrated similarity between each pixel and the stroke width patterns is namely an integrated computing result of all similarities between the pixel and all stroke width patterns.

Abstract: A information-hidden mobile ticketing system, having a ticket purchasing device, an mobile ticket issuance management system, a embedded mobile ticket, a mobile communication device, and a ticket verification device. The user can purchase a mobile ticket from the mobile ticket issuance management system via the ticket purchasing device. Once the purchasing information is provided, the mobile ticket can be sent in the form of a message, a multi-medium message or other wireless form to a mobile communication device assigned by the purchaser. The information hiding method is used to embed the barcode representing the mobile ticket in a digital image. By a program specified by the mobile communication device, the digital image can be retrieved. Thereby, the risk of being decoded and stolen can be alleviated.

Abstract: An electronic ticket service system based on color scale image recognition for individual identification, purchasing certificate or bill payment. Different from the conventional black-and-white one- or two-dimensional barcode, the color scale uses assembly of color scales for various colors. Each assembly of multiple color scales represents one element, such that the information capacity is greatly increased. The user can order the ticket via phone or internet. When the user has successfully input the purchase information and complete the payment procedure, the electronic ticket service center can issue and transmit the electronic ticket containing the color scale code to the assigned device through multimedia or wireless transmission. The assigned device can be cellular phones or other mobile communication terminal devices. Upon entrance, the electronic ticket displayed by the cellular phones or the mobile communication terminals is verified by a ticket verification device.

Abstract: A string extraction method for an image based on multiple stroke width patterns matching is provided. The string extraction method includes matching each possible stroke width pattern with an input image for obtaining the similarities between the width patterns and each pixel, wherein the integrated similarity between each pixel and the stroke width patterns is namely an integrated computing result of all similarities between the pixel and all stroke width patterns.

Abstract: An innovative method of automatic container number recognition is described, the container number recognition work is carried out respectively with reference to three component color red(R), green(G), and blue(B) grey level pixel maps, and then the identified results are reorganized. Since the synthesized three component color R, G, B grey level pixel map is obtained by mixing R, G, B color component according to a definite proportion (for example dividing the sum of three components by 3), hence among the three component color grey level pixel maps, there must be at least one (R, or G, or B) whose contrast is better than that of the synthesized one. This most confidential one is picked out as the final result of the container number recognition.

Abstract: A personal identification system based on the reading of multiple one-dimensional barcodes scanned from PDA/cell phone screen, which is a personal identification system applicable for reading multiple one-dimensional barcode on PDA/cell phone screen, comprises a multiple one-dimensional barcode generating system and a reading system of multiple one-dimensional barcode on PDA/cell phone screen, wherein said multiple one-dimensional barcode generating system is consisted of a data input unit and a barcode generating unit. The reading system of multiple one-dimensional barcode on PDA/cell phone screen is consisted of a PDA/cell phone reaction unit, a CCD camera, a frame grabber, an image processing unit, a barcode recognition unit and a data recording unit. The personal identification system based on the reading of multiple one-dimensional barcodes scanned from PDA/cell phone screen is useful as the mechanism for personal identification, certificates of purchase or checkoff.