Analog Devices,inc.

Analog Devices International Unlimited Company

Analog Devices Global

Rajesh Mahapatra

Raka Singh

Gaurav Malik

Gopal Karanam

Michael L Long

Sudong Shu

Akshayakumar Haribhatt

Rajesh Vijayakumar

Qian Zhang

Raghavendra Habbu

This disclosure describes techniques to aggregate sensor data. The techniques perform operations comprising: receiving, from a first sensor, a first profile representing a first set of movement attributes detected by the first sensor in an area at a given point in time; receiving, from a second sensor, a second profile representing a second set of movement attributes detected by the second sensor in the area at the given point in time; computing a similarity measure between the first and second sets of movement attributes of the first and second profiles; determining that the similarity measure exceeds a threshold value; and in response to determining that the similarity measure exceeds the threshold value, associating the first and second profiles with a same first object that is in the area at the given point in time.

Aggregating sensor profiles of objects

This disclosure describes techniques to count objects in an area. The techniques include operations comprising: receiving, from a first sensor, data that identifies a location of a first object in an area at a given point in time; receiving, from a second sensor, data that identifies a location of a second object in the area at the given point in time; and aggregating the data from the first sensor and the data from the second sensor to compute a count value indicating how many objects are present in the area at the given point in time.

Multiple sensor aggregation

A system and method for removing noise from images are disclosed herein. An exemplary system includes an edge-detection-based adaptive filter that identifies edge pixels and non-edge pixels in an image and selects a filtering technique for at least one non-edge pixel based on a comparison of the at least one non-edge pixel to a neighboring pixel region, wherein such comparison indicates whether the at least one non-edge pixel is a result of low-light noise.

System and method for removing image noise

A line-detection system computes, using a local memory, a result of a partial conversion of image-space pixel data from image space to Hough space. The result is analyzed for edges corresponding to a line present in the partial conversion. The line is compared against other lines detected in previously computed partial results to identify a longest line in the image.

Dynamic line-detection system for processors having limited internal memory

In general, in one embodiment, low-light noise is removed from an image by separately filtering luma and chroma components of the image, by adaptively filtering the image based at least in part on a Gaussian distribution of the image, and/or by dividing the image into separate regions and filtering each region separately.

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Bengaluru, India

Rajesh Mahapatra