Interra Systems, Inc.

Rishi Gupta

Shekhar Madnani

Bhupender Kumar

Pervez Alam

Advait Madhav Mogre

Paras Garg

Raman Kumar Gupta

Kushal Ghosh

Advait Mogre Madhav

A system and a method for searching an image within another image are disclosed. The method includes producing template edge images and target edge images, having image scales, based on determination of edge gradients of a template image and a target image in one or more directions. The template image indicates an image to be searched. The target image indicates another image within which the image needs to be searched. Further, images comprising correlation coefficient values are produced for each of the directions by computing correlation coefficients between the template edge images and the target edge images. At least one local peak is identified from each of the images comprising the correlation coefficient values. Spatial locations along with the correlation coefficients corresponding to the local peak are determined. Thereafter, a presence of the template image in the target image is identified based upon an intersection of the spatial locations.

System and method for searching an image within another image

A system and a method for detecting presence of a living hold in a video stream are disclosed. The method comprises pre-processing N consecutive frames for eliminating noise. An edge score may be calculated for the N consecutive frames, and a clip threshold primary and a clip threshold secondary may be defined. The method further comprises identifying primary edges and secondary edges in the N consecutive frames. Successively, a percentage of fixed primary edges and percentage of fixed secondary edges may be determined. Presence of the living hold may be confirmed based on the value of the percentage of fixed primary edges and the percentage of fixed secondary edges.

System and method for detecting presence of a living hold in a video stream

A method and system detection of inherent noise present within a video source prior to digital video compression is disclosed. A noise image is extracted by subtracting a current image from its filtered version. Each pixel of the extracted noise image is normalized based on a determined principal edge image and the analog noise pixels are accumulated to generate an intermediate noise confidence value. Analog noise may be detected based on an analog noise confidence value generated based on the intermediate noise confidence value and a ringing metric, a blockiness metric, a motion vector cost of the current image, a blurriness exception weight, a flashiness exception weight, and a pan blur exception weight. The method may further comprise detection of high frequency noise based on determining a high frequency noise confidence value that may be based on a high frequency noise value and a frequency component with highest magnitude.

Method and system for detection of inherent noise present within a video source prior to digital video compression

A method and system for ghost detection in an image are described. Initially, a mode for detecting ghosting artifact is determined for deciding whether to perform analog or inter field ghosting analysis on the image. Based on the determined mode, a plurality of fields is determined to generate a field overlay image. The image is updated based on the field overlay image and an inter-field average of absolute difference is computed. A significant edge image, a principal edge image, and a delta gradient image are generated. A confidence score indicative of a likelihood of ghosting artifact in the image, is computed based on at least the inter-field average of absolute difference, a first and a second count of pixels in the delta gradient image, a third count of pixels in the principal edge image, and a count of rows of the significant edge image that correspond to the ghosting artifact.

Method and system for detection of ghosting artifact in a video

A method and system for determining blur in digital video due to high quantization adopted during encoding of an image. The image is preprocessed to filter the noise and an edge image is extracted from the preprocessed image. A gradient sign change is determined for each pixel of the edge image. A ringing metric is determined based on the gradient magnitude and the gradient sign change. Further, a blockiness metric is determined based on a block grid periodicity and offset that is determined based on block grid analysis of the edge image. Further, a perceptual blurriness metric is determined using a mean and kurtosis computed based on a gradient histogram analysis of the block grid analysed edge image. A composite blurring metric is determined based on the blockiness metric, the perceptual blurriness metric, and ringing metric.

Methods and systems for detection of blur artifact in digital video due to high quantization

The present invention relates to computation of digital fingerprint of a video sequence. The invention presents systems and methods for quick identification of shot boundaries and extraction of fingerprints by processing one or more specific frames. The systems and methods are applied on uncompressed video or compressed video having inter-frame or intra-frame compression. The methods comprises of comparing two frames of the video having a gap in between and identifying a specific frame present in between the two frames such that the specific frame may have a shot boundary. Shot boundaries are calculated for the entire video and then a fingerprint is generated using all the shot boundaries present in the video.

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Noida, India

Rishi Gupta