Interra Systems, Inc.

Other

Bhupender Kumar

Shekhar Madnani

Rishi Gupta

Advait Madhav Mogre

Pervez Alam

Paras Garg

Alok Kumar

Akshi Raina

Advait Mogre Madhav

Raman Kumar Gupta

Sugeet Singh Saini

A system and method for identifying presence of digital ghosting artifacts in videos is disclosed. The method comprises estimating a blending parameter (&#x3b1;) for a current image using a previous image and a next image of a digital video stream. Successively, a blended image (B) is created by mixing contents of the previous image and the next image based on the estimated blending parameter (&#x3b1;). Thereafter, a first similarity is computed between the blended image (B) and a de-interlaced image (C), based on a Normalized Cross Correlation (NCC) between multiple blocks of the blended image (B) and the de-interlaced image (C). Successively, a second similarity is computed between the blended image (B) and the de-interlaced image (C), based on values of standard deviation of an absolute difference frame determined between the blended image (B) and the de-interlaced image (C). The de-interlaced image (C) is finally identified to comprise digital ghosting artifact based on values of the first similarity and the second similarity.

System and method of identifying presence of digital ghosting artifacts in videos

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 adjusting luminance flashes in a video stream are disclosed. The method includes identifying a sequence of frames, having the luminance flashes, from the video stream. The sequence of frames is extended at both sides (start and end) based on a predefined threshold. The method further comprises dividing an extended sequence of frames into at least three segments. Further, the method includes determining a correction factor and a correction constant for each of the at least three segments. Thereafter, the method includes modifying luminance values of pixels of each of the at least three segments based on the correction factor and the correction constant, thereby adjusting the luminance flashes in the video stream.

System and method for correcting photosensitive epilepsy luminance flashes in a video

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 for detection of artifacts in a video after application of an error concealment strategy by a decoder is disclosed. An absolute difference image is determined by subtraction of a current image and a previously decoded image. A threshold marked buffer is determined to replace the pixel values of the absolute difference image with a first pixel value or a second pixel value, based on comparison of pixel values with a first predefined threshold. A candidate region is determined by determining a pair of edges of the threshold marked buffer having length above a second predefined threshold, distance between them above a third predefined threshold, and pixel values between them in the absolute difference image, less than a fourth predefined threshold. Validation of candidate region is based on comparison of characteristics of the candidate region with characteristics of the current image and/or previously decoded images.

Methods and systems for detection of artifacts in a video after error concealment

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

A method and a system implementing the method for detecting presence of burnt-in text in a video sequence are described. Initially, possible text candidates are separated from the background information. Individual candidates are then validated against the character features like similar font width, resolution, width height ratio, etc. These characters are further validated for the formation of words/sentences. Finally, the temporal features are used for validation for determining valid burnt-in text candidates.

Systems and methods for detection of burnt-in text in a video

Methods and systems for detecting block based video dropouts in one or more fields associated with various video frames is provided. A current field is divided into a plurality of blocks. A set of activity blocks is identified from the plurality of blocks. The activity blocks are then processed to identify horizontal and vertical lines which are then further processed to form one or more candidate error blocks. The candidate error blocks are validated for start and end to determine a count of video dropout errors associated with the current field.

Methods and systems for detection of block based video dropouts

A system and method for detecting artifacts in a video having a sequence of pictures is described. The method comprises the steps of calculating a motion vector cost and a variable threshold for each of the pictures. In case, the motion vector cost for the picture is greater than the variable threshold of the picture, then a first scene change profile and a second scene change profile for the picture is computed and analyzed for determining the character of the variation in the motion vector cost. An artifact metric for the picture is also calculated and the artifact metric for the picture is compared with a programmable artifact reporting threshold for ascertaining if an artifact is present in the video. The described approach is generic in nature and takes into account various exceptions that may be present within a picture that may be similar in character as an artifact.

Methods and systems for detecting video artifacts

Systems and methods for detecting defective pixels in a video sequence having a plurality of frames, the method comprising determining one or more frames of a single scene and determining a plurality of buffers of each frame related to the single scene, detecting one or more candidate pixels for a first predefined number of frames, tracking the detected one or more candidate pixels for a second predetermined number of frames, validating the one or more candidate pixels for presence of defect and marking a candidate pixel from the one or more candidate pixels as a defective pixel based on one or more predefined conditions.

Systems and methods for detecting defective pixels in a video sequence

Systems and methods for detecting chroma dropout errors in one or more fields associated with various video frames are provided. Pixels associated with a current field are divided into a set of pixel pairs. Co-occurrences matrices are calculated for previous and subsequent fields. A first pixel pair associated with the current field is selected. First and second set of entries are selected from the co-occurrence matrices corresponding to the previous and subsequent fields. The first pixel pair is searched in the first and second set of entries. An absence of the first pixel pair in the first and second set of entries satisfies a first criterion of chroma dropout error. Other criteria in addition to the first criterion are evaluated to label the first pixel pair as erroneous.

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Palwal, India

Bhupender Kumar