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SNELL LTD

Overview
  • Total Patents
    112
  • GoodIP Patent Rank
    72,165
About

SNELL LTD has a total of 112 patent applications. Its first patent ever was published in 2003. It filed its patents most often in United States, EPO (European Patent Office) and United Kingdom. Its main competitors in its focus markets audio-visual technology, computer technology and telecommunications are FORCHHEIMER ROBERT, NINGBO HUAGAO INFORMATION TECH CO LTD and Shanghai fullhan microelectronics co ltd.

Patent filings per year

Chart showing SNELL LTDs patent filings per year from 1900 to 2020

Top inventors

# Name Total Patents
#1 Knee Michael James 34
#2 Weston Martin 27
#3 Diggins Jonathan 25
#4 Butters Jeff 5
#5 Jonathan Diggins 4
#6 Michael James Knee 4
#7 Diggins Joe 4
#8 Snell Maurice 3
#9 Martin Weston 3
#10 Phillips Gerard 3

Latest patents

Publication Filing date Title
GB201412488D0 Representing an object in an image
GB201411192D0 Hash-based media search
GB201402775D0 Method and apparatus for managing audio visual, audio or visual content
GB201321827D0 Adjusting occupancies of a set of buffers
GB201320124D0 Method and apparatus for processing a switched audio signal
GB201309489D0 Image processing
GB201213358D0 Determining the value of a specified quantile using iterative estimation
GB201206067D0 Selecting motion vectors on the basis of acceleration
GB201200654D0 Determining aspect ratio for display of video
GB201106029D0 Controlling the timed release of multimedia content, synchronising unscheduled (user-accessed) multimedia content and scheduled broadcast content
GB201104159D0 Analysis of stereoscopic images
GB201015089D0 Detecting stereoscopic images
GB201011603D0 Methods and apparatus for resampling a spatially sampled attribute of an image
GB201007254D0 Motion estimation
GB201005986D0 Repairing scratch impairments to an image
GB201004539D0 Analysis of stereoscopic images
GB201002865D0 Objective picture quality measurement
GB0922160D0 Changing the temporal sample rate of a motion image sequence
GB0917706D0 Defining image features using local spatial maxima and minima
GB0914638D0 Correcting image defects using a gradient measure