Industrial Technology Research Institute

Ipreg Inc.

Ipreg Incorporation

Chung-Hsien Huang

Ming-Yu Shih

Ruei-Cheng Wu

Yi-Ta Wu

Cheng-Chuan Chou

Chao-Hung Kao

Bor-Ran Li

Ching-Wen Chang

Chen-Yen Chung

Bor-ran Li

The present invention provides a sperm sorting chip and a method for sorting sperm using the same. Said sperm sorting chip includes: a flow channel structure sequentially configured with a gradually diverging flow field region, a main flow channel, and a gradually converging main flow channel intercommunicated with each other from a first side end to a second side end; a fluid injection port, a semen injection port, and a semen extraction port separately located at the first side end and communicated with a main input channel of the gradual diverging flow field region; and a waste fluid outlet located at the second side end and communicated with the gradually converging main flow channel. The gradually diverging flow field region further includes a plurality of sub-input channels derived from the main input channel and converged into the main flow channel, and the plurality of sub-input channels have a gradually widening channel width at the junction with the main flow channel. By contrast, the gradually converging main flow channel has a gradually narrowing channel width toward the waste fluid outlet.

Sperm sorting chip and method for sorting sperm using the same

An image-based detecting system for traffic parameters first sets a range of a vehicle lane for monitoring control, and sets an entry detection window and an exit detection window in the vehicle lane. When the entry detection window detects an event of a vehicle passing by using the image information captured at the entry detection window, a plurality of feature points are detected in the entry detection window, and will be tracked hereafter. Then, the feature points belonging to the same vehicle are grouped to obtain at least a location tracking result of single vehicle. When the tracked single vehicle moves to the exit detection window, according to the location tracking result and the time correlation through estimating the information captured at the entry detection window and the exit detection window, at least a traffic parameter is estimated.

Image based detecting system and method for traffic parameters and computer program product thereof

In one exemplary embodiment, a tracking system for region-of-interest (ROI) performs a feature-point detection locally on an ROI of an image frame at an initial time via a feature point detecting and tracking module, and tracks the detected features. A linear transformation module finds out a transform relationship between two ROIs of two consecutive image frames, by using a plurality of corresponding feature points. An estimation and update module predicts and corrects a moving location for the ROI at a current time. Based on the result corrected by the estimation and update module, an outlier rejection module removes at least an outlier outside the ROI.

Tracking system and method for regions of interest and computer program product thereof

An object tracking method for a non-overlapping-sensor network works in a sensor network. The method may comprise a training phase and a detection phase. In the training phase, a plurality of sensor information measured by the sensors in the sensor network is used as training samples. At least an entrance/exit is marked out within the measurement range of each sensor. At least three characteristic functions including sensor spatial relation among the sensors in the sensor network, difference of movement time and similarity in appearance, are estimated by an automatically learning method. The at least three characteristic functions are used as the principles for object tracking and relationship linking in the detection phase.

Object Tracking method and apparatus for a non-overlapping-sensor network

An apparatus and method for moving object detection computes a corresponding frame difference for every two successive image frames of a moving object, and segments a current image frame of the two successive image frames into a plurality of homogeneous regions. At least a candidate region is further detected from the plurality of homogeneous regions. The system gradually merges the computed frame differences via a morphing-based technology and fuses the merged frame difference with the at least a candidate region, thereby obtaining the location and a complete outline of the moving object.

Apparatus and method for moving object detection

A pixel region-based image segmentation method is disclosed. When an input image is retrieved, pixels thereof are sequentially scanned row by row. Signs of unmarked pixels of the input image are determined according to region features of neighboring pixels of each pixel and pixel update information is recorded to generate a region sign update data table and a region sign feature data table. The pixels of the input frame are further scanned row by row to retrieve signs of the pixels and region signs of the pixels are determined and updated according to the region sign update data table.

Image segmentation method and system based on region features of pixels

A method for tracking a moving object is provided. The method detects the moving object in a plurality of continuous images so as to obtain space information of the moving object in each of the images. In addition, appearance features of the moving object in each of the images are captured to build an appearance model. Finally, the space information and the appearance model are combined to track a moving path of the moving object in the images. Accordingly, the present invention is able to keep tracking the moving object even if the moving object leaves the monitoring frame and returns again, so as to assist the supervisor in finding abnormal acts and making following reactions.

Method for tracking moving object

A method for detecting a shadow of an object in an image is provided. A moving object in a plurality of continuous images is detected. A histogram of a color variation of the moving object in each of the images is calculated. The histograms of the color variation are accumulated to obtain a cumulative histogram. A distribution of the color variation in the cumulative histogram is estimated to obtain a shadow distribution function. Whether each pixel in a received image belongs to the shadow is determined by using the shadow distribution function.

Growing community of inventors

Tainan, Taiwan

Chung-Hsien Huang